U.S. patent application number 11/973615 was filed with the patent office on 2008-10-23 for systems and methods for geographic positioning using radio spectrum signatures.
Invention is credited to Glenn Patrick Hauck, Dan John Glen Nephin, Jackson Kit Wang.
Application Number | 20080258974 11/973615 |
Document ID | / |
Family ID | 36583169 |
Filed Date | 2008-10-23 |
United States Patent
Application |
20080258974 |
Kind Code |
A1 |
Wang; Jackson Kit ; et
al. |
October 23, 2008 |
Systems and methods for geographic positioning using radio spectrum
signatures
Abstract
Methods, radios, components thereof, and other devices for
localizing a geographic position of a radio receiver are provided.
A current radio signature is obtained. The current radio signature
comprises a plurality of measured signal qualities that
collectively represent a frequency spectrum. Each measured signal
quality in the plurality of measured signal qualities corresponds
to a portion of the frequency spectrum. The current radio signature
is compared with a plurality of reference radio signatures. Each
reference radio signature in the plurality of reference radio
signatures is associated with a global position. When the comparing
identifies a unique match between the current radio signature and a
reference radio signature in the plurality of reference radio
signatures, the radio receiver is deemed to be localized to the
global position associated with the reference radio signature.
Inventors: |
Wang; Jackson Kit; (Toronto,
CA) ; Hauck; Glenn Patrick; (East York, CA) ;
Nephin; Dan John Glen; (Toronto, CA) |
Correspondence
Address: |
JONES DAY
222 EAST 41ST ST
NEW YORK
NY
10017
US
|
Family ID: |
36583169 |
Appl. No.: |
11/973615 |
Filed: |
October 9, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11011222 |
Dec 13, 2004 |
7298328 |
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11973615 |
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Current U.S.
Class: |
342/451 ;
342/450 |
Current CPC
Class: |
G01S 5/0252
20130101 |
Class at
Publication: |
342/451 ;
342/450 |
International
Class: |
G01S 3/02 20060101
G01S003/02; G01S 3/72 20060101 G01S003/72 |
Claims
1-53. (canceled)
54. A radio having a memory, the memory comprising: a radio
signature lookup table, said radio signature lookup table
comprising a plurality of reference radio signatures, each
reference radio signature in said plurality of reference radio
signatures associated with a global position; means for localizing
a geographic position of the radio comprising instructions for
obtaining a current radio signature by scanning a contiguous range
of frequencies in said frequency spectrum, wherein said current
radio signature comprises a plurality of measured signal qualities
that collectively represent said frequency spectrum, each measured
signal quality in said plurality of measured signal qualities
corresponding to a portion of said frequency spectrum; means for
comparing said current radio signature to said plurality of
reference radio signatures; a radio display table, wherein said
radio display table comprises information for each global position
in a plurality of global positions; and means for updating
information in said radio display table.
55. The radio of claim 54, the memory further comprising: means for
obtaining information from said radio display table as a function
of an identity of a reference radio signature uniquely identified
by said means for comparing.
56. (canceled)
57. The radio of claim 54, the memory further comprising means for
updating a reference radio signature in said radio signature lookup
table.
58. The radio of claim 54, wherein said radio signature lookup
table and said means for localizing a geographic position of the
radio are embedded in one or more application specific integrated
circuits (ASICs) or field-programmable gate arrays (FPGAs).
59-64. (canceled)
65. The radio of claim 54, the memory further comprising means for
populating said radio signature lookup table.
66. The radio of claim 65, wherein a reference radio signature in
said radio signature lookup table is populated by said instructions
for populating using a propagation model.
67. The radio of claim 65, wherein a reference radio signature in
said radio signature lookup table is populated by said instructions
for populating using an empirical model.
Description
1. FIELD OF INVENTION
[0001] The present invention relates to the determination of the
location of a radio receiver by comparing a measured radio
signature to a lookup table comprising a plurality of radio
signatures from known locations.
2. BACKGROUND OF INVENTION
[0002] Present techniques for locating electronic devices (e.g.,
cellular phone, personal digital assistants, computer, etc.)
require technology such as (i) satellite signals (global
positioning signals "GPS"), (ii) GPS and assistance via cellular
signals to penetrate, building structures, or (iii) triangulation
using a cellular system. Each of these techniques, while useful in
their own right, has the drawback that they require relatively
expensive equipment and/or a subscription to an expensive data
service. What is needed in the art are cheaper methods for locating
the global position of an electronic device.
3. SUMMARY OF INVENTION
[0003] The present invention addresses the shortcomings found in
the prior art. The present invention provides a mechanism for
determining the geographic position of an electronic device using
radio signals. One embodiment of the present invention provides a
method of localizing a geographic position of a radio receiver. In
the method, a current radio signature is obtained. This current
radio signature comprises a plurality of measured signal qualities
that collectively represent a frequency spectrum. Each measured
signal quality in the plurality of measured signal qualities
corresponds to a portion of the frequency spectrum. The current
radio signature is compared to a plurality of reference radio
signatures. Each reference radio signature in the plurality of
reference radio signatures is associated with a global position.
When the comparing identifies a unique match between the current
radio signature and a reference radio signature in the plurality of
reference radio signatures, the radio receiver is deemed to be
localized to the global position associated with the reference
radio signature.
[0004] In some embodiments, the frequency spectrum is all or a
portion of the FM frequency spectrum, all or a portion of the AM
frequency spectrum, all or a portion of the spectrum between 300
KHz and 3 MHz, all or a portion of the spectrum between 3 MHz and
30 MHz, or a portion of the spectrum between 30 MHz and 300 MHz, or
all or a portion of the spectrum between 300 MHz and 3000 MHz. In
some embodiments, a measured signal quality in the plurality of
measured signal qualities is a decibel rating of a frequency in the
frequency spectrum. In some embodiments, the measured signal
quality in the plurality of measured signal qualities is a voltage
representing a frequency in the frequency spectrum.
[0005] In some embodiments, the portion of the frequency spectrum
corresponding to a first measured signal quality in the plurality
of measured signal qualities is a first frequency window. In some
embodiments, this first frequency window comprises a frequency
spectrum that has a spectral width that is between 1 KHz and 200
KHz or between 200 KHz and 400 KHz. In some embodiments, the
portion of the frequency spectrum corresponding to a second
measured signal quality in the plurality of measured signal
qualities is a second frequency window and a spectral width of the
first frequency window and the second frequency window is the same
or different.
[0006] In some embodiments, the first measured signal represents a
strongest observable signal in the portion of the frequency
spectrum corresponding to the first measured signal quality. In
some embodiments, a second measured signal quality also corresponds
to the first frequency window. In some embodiments the first
measured signal quality and the second signal quality are each
independently selected from the group consisting of an RDS quality,
an FM multipath reading, FM level, AM level, or a phase lock.
[0007] Another aspect of the invention provides a device comprising
instructions for accessing a radio signature lookup table. The
radio signature lookup table comprises a plurality of reference
radio signatures that collectively represent a frequency spectrum.
Each reference radio signature in the plurality of reference radio
signatures is associated with a global position. The device further
comprises a radio signature measurement model for localizing a
geographic position of a device. The radio signature measurement
model comprises instructions for obtaining a current radio
signature. The current radio signature comprises a plurality of
measured signal qualities. Each measured signal quality in the
plurality of measured signal qualities corresponds to a portion of
the frequency spectrum. The device further comprises a radio
signature comparison module having instructions for comparing the
current radio signature to the plurality of reference radio
signatures.
[0008] In some embodiments, the device further comprises
instructions for accessing a radio display table. This radio
display table comprises information for each global position in a
plurality of global positions. Such embodiments further include a
radio display module for obtaining information from the radio
display table as a function of an identity of a reference radio
signature uniquely identified by the instructions for comparing. In
some embodiments, the device further comprises a table update
module. The table update module comprises instructions for updating
information in the radio display table. In some embodiments, the
device further comprises a table update module. The table update
module comprises instructions for updating a reference radio
signature in the radio signature lookup table. The instructions for
accessing a radio signature lookup table and the radio signature
measurement model is embedded in one or more application specific
integrated circuits (ASICs), one or more field-programmable gate
arrays (FPGAs), or any combination thereof. In some embodiments,
the device comprises an ASIC or FPGA. In some embodiments, the
device is a component of an RDS or an HD radio.
[0009] Another aspect of the invention comprises a radio comprising
means for accessing a radio signature lookup table. The radio
signature lookup table comprises a plurality of reference radio
signatures. Each reference radio signature in the plurality of
reference radio signatures is associated with a global position.
The radio further comprises means for localizing a geographic
position of the radio. The radio signature measurement model
further comprises instructions for obtaining a current radio
signature. This current radio signature comprises a plurality of
measured signal qualities that collectively represent a frequency
spectrum. Each measured signal quality in the plurality of measured
signal qualities corresponds to a portion of the frequency
spectrum. The radio further comprises means for comparing the
current radio signature to the plurality of reference radio
signatures.
4. BRIEF DESCRIPTION OF THE FIGURES
[0010] FIG. 1A illustrates a radio receiver capable of determining
geographical position in accordance with an embodiment of the
present invention.
[0011] FIG. 1B illustrates data structures that are measured by a
radio receiver capable of determining geographical position in
accordance with an embodiment of the present invention.
[0012] FIG. 2 illustrates a method for determining geographic
position in accordance with an embodiment of the present
invention.
[0013] FIG. 3 illustrates a method for assigning a global position
to a current radio signature in accordance with an embodiment of
the present invention.
[0014] FIG. 4 illustrates a circuit diagram for an exemplary system
for measuring signal strength across a spectrum of wavelengths for
use in populating a radio signature lookup table in accordance with
an embodiment of the present invention.
[0015] FIG. 5 illustrates a system component diagram for an
exemplary system for measuring signal strength across a spectrum of
wavelengths for use in populating a radio signature lookup table in
accordance with an embodiment of the present invention.
[0016] FIG. 6 illustrates a graphical user interface for monitoring
data used to populate a radio signature lookup table in accordance
with an embodiment of the present invention.
[0017] FIG. 7 illustrates measurements taken in a drive test in the
Waterloo area of Canada for an empirical model in accordance with
the present invention.
[0018] FIG. 8 illustrates measurements taken in a drive test in the
Waterloo area of Canada for an empirical model, after
normalization, in accordance with the present invention.
[0019] FIG. 9 illustrates FM frequency distribution for Canada and
the continental United States.
[0020] FIG. 10 illustrates signal strength plotted against distance
from the transmitter at the FM frequency 104.5 using a J2
elliptical model for the Earth to calculate the absolute distance
between the transmitter and receiver based on recorded GPS
coordinates.
[0021] FIG. 11 illustrates signal strength plotted against distance
from the transmitter at the FM frequency 97.3 using a J2 elliptical
model for the Earth to calculate the absolute distance between the
transmitter and receiver based on recorded GPS coordinates.
[0022] FIG. 12 illustrates measurements taken for a particular
frequency in a stationary test conducted in the Waterloo area, in a
relatively flat area with very little visible terrain variation and
almost no ground clutter in the immediate area.
[0023] FIG. 13 illustrates an unnormalized stationary FM signature
for a test location.
[0024] FIG. 14 illustrates a normalized stationary FM signature for
a test location.
[0025] Like reference numerals refer to corresponding parts
throughout the several views of the drawings.
5. DETAILED DESCRIPTION OF THE INVENTION
[0026] The present invention provides cost effective systems and
methods for determining the location and direction of motion of a
radio receiver. In the present invention, radio signal reception is
polled across a spectrum of frequencies. These measurements are
collectively termed a radio signature. This measured radio
signature is then compared to a plurality of reference radio
signatures. Each reference radio signature corresponds to a known
location. For example, a first reference radio signature in the
plurality of radio signatures corresponds to a first location and a
second reference radio signature in the plurality of radio
signatures corresponds to a second location. Direction can be
obtained as the radio receiver moves across boundaries between
locations with different reference radio signatures.
5.1 Exemplary Radio Receiver
[0027] Reference will now be made to FIG. 1A, which shows an
exemplary radio receiver 10 in accordance with an embodiment of the
present invention. Many aspects of radio receiver 10 are
conventional and will not be discussed so that the inventive
aspects of the present invention can be emphasized. In typical
embodiments, radio receiver 10 includes a radio signal decoder 12.
In preferred embodiments, radio signal decoder 12 can be controlled
by a microprocessor 14 to scan a predetermined range of frequencies
in order to measure signal strength across the range of
frequencies.
[0028] A commercial example of a radio signal decoder 12 is the
Microtune MT1390 FM module (Plano, Tex.). The MT1390 chip can be
electronically tuned to any given frequency in the FM band through
instructions sent to the chip by a microprocessor through an I2C
port. The MT1390 chip reports signal strength at the FM frequency
to which it is tuned. The MT1380 chip is designed to scan all
available frequencies to allow for continuous reception of data
from information systems such as Radio Data System (RDS). The RDS
radio signal combines an audio feed with small amounts of text and
data that can be picked up and processed by radios that have an RDS
decode, such as the MT1390, built-in. Such radio receivers can
display this information. The information commonly transmitted is
station name (e.g., an 8-digit radio station name, such as "BBC
R.4" or "Jazz FM"), program type (e.g. pop, rock, etc), a `TA flag`
that is switched on when a radio station starts a travel report,
and switched off at the end (used to automatically switch the RDS
radio to a station carrying travel news, or in a car, pause a
cassette or a CD, when local travel news is broadcast), radio text
(information that `scrolls` across RDS radio displays, providing
information that's sent from the radio station, an Enhanced Other
Networks flag (EON flag) that allows an RDS radio to know about
other associated stations, so a radio can know that when listening
to a first radio program, it should monitor a second radio station,
in case there's some travel news, an alternative frequency (AF)
flag that contains information about a station's other FM
frequencies, so that the radio can switch to a better signal while
driving, time and date (CF flag) that carries the current date and
time, resetting for daylights saving time, etc. Another example of
an RDS radio is the Sony ICF-M33RDS, and the Roberts R9929, R9940,
and R861. In other embodiments, radio signal decoder 12 is a high
definition (HD) radio decoder. Commercial examples of the HD radio
decoder include, but are not limited to, the Kenwood KTC-HR100 HD
Radi6 tuner.
[0029] In typical embodiments, radio signal decoder 12 serves as an
auxiliary radio tuner that functions as the `background` tuner
within radio receiver 10, scanning all available frequencies and
allowing for continuous reception of data from information systems
such as Radio Data System (RDS). As such, radio signal decoder 12
is typically combined with a primary radio tuner such as
Microtune's MT1383/1384 companion AM/FM tuners for a dual-tuner
AM/FM apparatus. The primary radio tuner is tuned by the user to
the desired radio frequency while the auxiliary radio tuner is used
to perform sweeps in accordance with the present invention and
obtain information from sources such as the Radio Data System.
[0030] In the present invention, radio signal decoder 12 can be
used to scan any portion of the FM frequency spectrum and/or the AM
frequency spectrum in order to measure a radio signature. In the
United States, the FM frequency spectrum is 88 megahertz (MHz) and
108 MHz. The AM frequency spectrum is generally between 520
kilohertz (KHz) and 1500 KHz. As such, radio signal decoder 12 can
be used to scan any portion (or all) of the frequency spectrum
between 520 KHz and 1500 KHz and/or between 88 MHz and 108 MHz. In
some embodiments, radio signal decoder 12 can be used to scan any
portion (or all) of the medium-frequency (MF) band, which has a
frequency range of between 300 KHz and 3 MHz, the high-frequency
(HF) band, which has a frequency range of between 3 MHz and 30 MHz,
the very-high frequency band (VHF) which has a frequency range of
between 30 MHz and 300 MHz, and/or the ultra-high-frequency (UHF)
band, which has a frequency rang of 300 MHz to 3000 MHz. For more
information on the possible bands that can be polled in order to
construct a radio signature in accordance with the present
invention, see Sinclair, 1997, How Radio Signals Work, McGraw-Hill,
New York, which is hereby incorporated by reference in its
entirety.
[0031] Microprocessor 14 can be a component of radio signal decoder
12 or a standalone component. In some embodiments, the
functionality of radio signal decoder 12 and/or microprocessor 14
is embedded in one or more application specific integrated circuits
(ASICs) and/or field-programmable gate arrays (FPGAs). In some
embodiments, microprocessor 14 is implemented as one or more
digital signal processors (DSPs). In these embodiments,
microprocessor 14 is considered any combination of chips, including
any combination of ASICs, FPGAs, DSPs, or other forms of microchips
known in the art. In general, any type of microarchitecture that
can store or access from memory approximately one megabyte of data
and has about one megaflop or greater of computing power is
suitable for implementing preferred embodiments of the present
invention.
[0032] Radio receiver 10 includes a display 16 for displaying the
RDS data feed and/or navigational information provided by the
present invention. In some embodiments, display 16 is an 8 to 16
character alphanumeric display. In other embodiments, display 16
supports between 8 and 100 characters. In still other embodiments,
display 16 is a graphical display.
[0033] Memory 20 can be random access memory (RAM). All or a
portion of this RAM can be on board, for example, an FPGA or ASIC.
In some embodiments, the RAM is external to microprocessor 14.
Alternatively, memory 20 is SDRAM available to a DSP or a FPGA that
has an embedded SDRAM controller. In some embodiments, memory 20 is
some combination of on-board RAM and external RAM. In some
embodiments memory 20 includes a read only memory (ROM) component
and a RAM component.
[0034] Memory 20 includes software modules and data structures that
are used by microprocessor 14 to implement the present invention.
While it is well known in the art that software modules and data
structures can be structured in many different ways in order to
implement a particular algorithm or method, one exemplary structure
has been provided in FIG. 1 in order to convey certain aspects of
the present invention. This exemplary structure includes a radio
signature measurement model 30 for measuring a radio signature. In
some embodiments, this measured radio signature is stored in memory
20 as current radio signature 50.
[0035] In some embodiments, memory 20 stores past radio signatures
60 in addition to the current radio signature 50. Past radio
signatures 60 can be used in the methods of the present invention
to establish the direction or to facilitate geographic positioning.
Memory 32 further comprises a radio signature comparison module 32
for comparing the current measured radio signature (and possibly
past measured radio signatures 60) to reference radio
signatures.
[0036] Memory 20 further comprises a radio display module 34 for
displaying information as a function of geographic position. For
example, consider the case in which radio signature comparison
module 32 determines that radio 10 is in geographic position one.
In such instances, radio display module 34 will display information
on display 16 associated with geographic position one. Then, when
radio signature comparison module 32 determines that radio 10 is in
geographic position two, module 34 will display information on
display 16 associated with geographic position two.
[0037] Memory 20 further comprises a table update module 36 for
updating radio signatures and global position specific information.
Table update module 36 typically receives updates to such
signatures from radio signals decoded by radio signal decoder 12.
Such updates are typically incremental in fashion. For example, if
the radio signature for a specific geographic location has changed
because a radio transmitter has gone on line (or off line), a data
feed in the radio signal decoded by radio signal decoder 12
transmits the updated radio signature and table update module 36
updates memory 20 accordingly.
[0038] In addition to the above-identified software modules, memory
20 comprises a radio signature lookup table 38. Radio signature
lookup table 38 includes a plurality of radio signatures 39. Each
radio signature 39 corresponds to a predetermined global position
62 (e.g., Chicago Ill.). In preferred embodiments, each radio
signature 39 corresponds to a geo-polygon that represents a region
with a distinct FM signature that has been generated by analyzing
overlapping transmitter broadcast regions. Each radio signature 39
includes a plurality of frequencies windows 40 and, for each such
frequency window 40, a signal quality 42. In typical embodiments,
frequency windows 40 are used to circumvent the effects of
phenomenon such as spectral leakage that occurs at frequencies
close to those of certain transmitters. Since FM transmitters in a
region are usually separated by more than 200 kHz, the occurrence
of an FM signal with two adjacent FM peaks is usually
representative of such spectral leakage. Such spectral leakage can
be observed by tuning a radio to the next possible FM channel and
discerning the sounds of an adjacent FM channel. Here, the term
spectral leakage is used loosely because it has not been determined
whether or not such effects are due to transmitter properties or to
receiver properties. That is, it is possible that tuner specific
hardware limitations cause this apparent problem. Radio signatures
39 can be referred to as reference radio signatures, and signal
qualities 42 can be referred to as reference signal qualities.
[0039] In some embodiments, only the maximum value within a given
frequency window 40 is considered the signal quality of the window.
The size of each frequency window 40 is chosen to reflect the
typical separation between active transmitter frequencies so that
true signal peaks are not removed from the signature. Thus, in some
embodiments, each frequency window 40 represents a predetermined
range of frequencies (window of frequencies) and the signal quality
42 corresponding to the frequency window 40 represents the
strongest observable signal in the range of frequencies. In some
embodiments, radio signature 39 spans all or a portion of the FM
frequency band and each frequency window 40 represents a range of
200 KHz. For example, a first frequency window 40 may represent all
frequencies between 88.0 MHz and 88.2 MHz, a second frequency
window 40 may represent all frequencies between 88.2 MHz and 88.4
MHz and so forth. In this example, the signal quality 42
corresponding to the first frequency window 40 is a value
representing the strongest measured signal between 88.0 MHz and
88.2 MHz for the corresponding geographical location, the signal
quality 42 corresponding to the second frequency window 40 is a
value representing the strongest measured signal between 88.2 MHz
and 88.4 MHz for the corresponding geographical location, and so
forth. In fact, FM signal strength (level) alone can potentially
yield one hundred plus frequency windows 40 of binning and 87.7 to
107.9 Mhz by 200 KHz is a well accepted frequency raster
spacing.
[0040] In some embodiments, each frequency window 40 represents a
frequency spectrum other than 200 KHz. In fact, the size of the
spectrum represented by a frequency window 40 is application
dependent. For example, in some embodiments, each frequency window
40 represents any frequency spectrum between 1 KHz and 200 KHz. In
other words, the frequency window 40 has a spectral width anywhere
between 1 KHz and 200 KHz. In some embodiments, each frequency
window 40 represents any frequency spectrum between 200 KHz and 400
KHz. In still other embodiments, each frequency window 40
represents any frequency spectrum between 400 KHz and 800 KHz.
However, in cases where the frequency band represented by radio
signature 39 is the FM band, frequency windows 40 representing a
frequency spectrum of 200 KHz is preferred.
[0041] In some embodiments, each frequency window 40 in radio
signature 39 is uniform. That is, each frequency window 40 has the
same spectral width (e.g., 200 KHz). In other embodiments, there is
no requirement that each frequency window 40 in radio signature 39
have uniform spectral width. For example, in some embodiments, a
radio signature 39 includes both AM and FM frequencies. In such
embodiments, frequency windows 40 centered on AM frequencies will
have one spectral width whereas frequency windows 40 centered on FM
frequencies will have a second spectral width. For instance, in a
preferred embodiment, the spectral width for frequency windows 40
in the FM band is 200 KHz whereas the spectral width for frequency
windows 40 in the AM band is 10 kHz.
[0042] In preferred embodiments, the plurality of frequency windows
40 in a given radio signature 39 define a contiguous spectral
region (e.g., all or a portion of the FM band). In some
embodiments, the plurality of frequency windows 40 in a given radio
signature 39 define two noncontiguous spectral regions (e.g., all
or a portion of the FM band plus all or a portion of the AM band).
In preferred embodiments, each radio signature 39 in lookup table
38 has the same frequency windows 40 as radio signature 50 and
optional radio signatures 60, thereby facilitating direct
comparison of radio signatures. In preferred embodiments, each
frequency window 40 uniquely represents a particular frequency
spectrum. In less preferred embodiments, there is overlap in the
frequency windows 40 of a radio signature 39. In some embodiments,
there are between five (5) and ten thousand (10,000) frequency
windows 40 in a radio signature 39. In more preferred embodiments,
there are between ten and five hundred frequency windows 40 in a
radio signature 39. In still more preferred embodiments there are
between 50 and 500 frequency windows 40 in a radio signature
39.
[0043] Signal quality 42 is any measure of signal quality.
Nonlimiting examples of signal quality 42 includes a decibel rating
and a voltage. In some embodiments, signal quality 42 is
represented in binary form where a first binary value represents a
signal quality 42 greater than some predetermined threshold value
and a second binary value represents a signal quality 42 that is
less than some predetermined threshold value.
[0044] In some embodiments, there are between five and one million
radio signatures 39 in radio signature lookup table 38. In more
preferred embodiments, there are between one hundred (100) and
fifty thousand (50,000) radio signatures 39 in radio signature
lookup table 38. In still more preferred embodiments, there are
between five hundred and twenty-five thousand radio signatures 39
in radio signature lookup table 38. In some embodiments, each radio
signature 39 corresponds to a unique global position (geographical
position) 62 in the United States, Canada, and/or Mexico. In some
embodiments, each radio signature 39 corresponds to a unique global
position in any combination of countries in the world.
[0045] In some embodiments, there are more than one radio
signatures 39 corresponding to the same unique global position 62
in lookup table. Certain embodiments include more than one radio
signature for a given global position to account for different
conditions (e.g., night time and day time, etc.).
[0046] In some embodiments, each frequency window includes more
than just one signal quality 42 attribute. For example, a generic
RDS radio receiver can yield the following output:
[0047] FM Frequency (e.g., float 87.5 to 108.0) MHz
[0048] RDS Quality (e.g., float 0.0000 to 5.0000) volts
[0049] FM Multipath (e.g., float 0.0000 to 5.0000) volts
[0050] FM Level (e.g., float 0.0000 to 5.0000) volts
In such a device, any combination of RDS quality (e.g., 0 to 5
volts), FM multipath (e.g., 0 to 5 volts) and FM signal strength
(FM level) (e.g., 0 to 5 volts) can be used as a metric to assess
quality in a given frequency window 40. In some HD specific
embodiments, atomic (GPS) time synchronized high density (HD)
signal markers present in the HD signal can be used, when such
signal markers become available.
[0051] Moreover, some devices that can serve as radio signal
decoder 12 and microprocessor 14 can measure additional variables
that are useful for establishing a metric that represents signal
quality in a given frequency window 40 (e.g., phase lock). Thus, in
some embodiments, signal quality 42 actually consists of
measurements for several different variables (e.g., RDS quality, FM
Mulipath, FM level, AM level, phase lock). In some embodiments,
each of these variables are combined to form a single
representation of signal quality for a given frequency window 40.
In other embodiments, each of these variables independently serves
as a unique representation of signal quality. In such embodiments,
signal quality 42 for a given frequency window 40 is
multidimensional.
[0052] In some embodiments, radio signature comparison module 32
determines the global position 62 of radio 10 at a given point in
time and radio display module 34 (which may be a subset of radio
signature comparison module 32) displays this global position 62 on
display 16. In some optional embodiments, radio display module 34
uses the newly determined global position 62 to see if there is any
information for the position 62 stored in optional radio display
table 70. Radio display table 70 includes records 72 for a
plurality of global positions. If radio display module 34 finds a
match between the newly identified global position 62 and a record
72 (i.e., the record 72 corresponds to the global position 62),
then module 34 displays record 72 on display 16. In some
embodiments, record 72 provides traffic or weather information for
the global position corresponding to record 72. In some
embodiments, record 72 provides a detailed street map for the
global position corresponding to record 72. Radio display table 70
is updated by table update module 36 using information provided by
radio waves decoded by radio signal decoder 12. Such updates can
include, for example, updated traffic information and/or updated
weather information for specific global positions.
5.2 Exemplary Data Structures
[0053] Referring to FIG. 1B, as a result of measurements obtained
by radio signal decoder 12, elements of a current radio signature
50 data structure are populated. That is, for each of a plurality
of frequency windows 82, one or more signal quality parameters 84
are determined. As in the case of signal quality parameters 42 of
FIG. 1A, there may be more than one signal parameter for each
frequency window 82 and the signal quality may represent a maximum
value for a given frequency window. In preferred embodiments there
is a one to one correspondence between respective frequency windows
82 of FIG. 1B and frequency windows 40 of FIG. 1A. In other words,
for each respective frequency window 82 of radio signature 50,
there is a corresponding frequency window 40 that represents the
same frequency spectrum as the respective frequency window 82.
5.3 Exemplary Method for Localizing a Radio Receiver
[0054] Now that an overview of a radio receiver 10 in accordance
with one embodiment of the present invention has been described
with reference to FIG. 1, a method of using the radio receiver 10
to identify the global position of the radio receiver in accordance
with one embodiment will be described in conjunction with FIG.
2.
[0055] Step 202. In step 202, a determination is made of the
current radio signature 50. This is accomplished by scanning a
predetermined range of frequencies. As discussed above, the present
invention envisions a broad spectrum of different possible
predetermined frequency ranges. However, in a preferred embodiment,
the predetermined range of frequencies is the FM band. The
predetermined range of frequencies is divided into a plurality of
predetermined frequency windows 82 that collectively represent the
predetermined range of frequencies. For each frequency window 82 in
the predetermined range of frequencies, a signal quality is
measured and saved as the corresponding signal quality 84 for the
frequency window. In some embodiments, this signal quality
represents the maximum field/signal strength measured in the
frequency window. For example, in some embodiments, radio signal
decoder 12 is a generic programmable RDS radio module that reports
FM signal quality as an analog value within a voltage range (e.g. 0
to 5 volts). In some embodiments, metrics in addition to or instead
of FM signal quality are used to assess a given frequency window
82. For example, in some embodiments an FM multipath signal is
measured in addition to FM signal quality. In some embodiments an
RDS quality is measured in addition to FM signal quality. For
example, a generic RDS radio receiver can report the RDS signal
quality as analog values in a predefined voltage range (e.g., 0 to
5) volts. In other embodiments, phase lock and other statistical
information provided by radio signal decoder 12 are recorded for
each radio signature 39 in step 202. For those variables that vary
as a function of frequency, the variables are recorded for each
frequency window 82. For those variables that do not vary as a
function of frequency, a signal measurement of such variables is
recorded for the radio signature 39.
[0056] In some embodiments, for each frequency in the predetermined
range of frequencies, the parameter of interest (e.g., FM radio
signal strength) is measured several different times. For each
measurement, the value assigned to the parameter of interest at the
given frequency is the average, median, or mean of the individual
values measured for the parameter of interest at the given
frequency. In some embodiments, such measurements are performed in
a sweep. For example, in some embodiments, the predetermined range
of frequencies is measured in a sweep. The sweep begins at one end
of the predetermined range of frequencies and finishes at the other
end of the predetermined range. Measurements of the parameters
needed to assess signal quality are performed at each frequency in
the predetermined range of frequencies. For example, in some
embodiments, the predetermined range of frequencies is the entire
FM band.
[0057] Step 202 begins at one end of the band (e.g., 88.0 MHz) and
takes samples at that frequency for a period of time, moves to the
next frequency in the band (e.g., 88.2 MHz) and takes samples at
that frequency for a period of time, and so forth. In some
embodiments, the period of time spent at each frequency (or
frequency window 82) is one second. In some embodiments, the period
of time spent at each frequency (or frequency window 82) is less
than 1 second, less than 0.5 seconds, or less than 100
milliseconds. In still other embodiments, the period of time spent
at each frequency (or frequency window 82) is more than 1 second,
more than 2 seconds, or more than 5 seconds). In some embodiments,
1000 samples of the parameter of interest are taken per second.
Thus, in an embodiment in which the period of time spend at each
frequency (or frequency window 40) is 1 second, 1000 samples
(measurements) are taken of the parameter of interest per second.
In some embodiments, more than one parameter is measured
simultaneously. In many instances, the capabilities of the radio
signal decoder 12 will dictate whether or not parameters can be
concurrently sampled, which parameters can be sampled, and how
frequently such parameters can be sampled. However, at a minimal
level, a parameter that is indicative of signal strength is
measured at each frequency or frequency window. In some
embodiments, between 10 and 10,000 samples per second are taken of
a parameter of interest during a sweep. In more preferred
embodiments, between 100 and 5,000 samples per second are taken of
a parameter of interest during a sweep.
[0058] In some embodiments, successive instances of step 202 are
performed at timed intervals. For example, step 202 is performed
every second, every minute, half hour, or some longer interval.
When step 202 is repeated, the values for current radio signature
may change subject to new measurements from radio signal decoder
12. Referring to FIG. 1B, in some embodiments, the current radio
signature 50 is saved as a past radio signature 60 prior to saving
new values for current radio signature 50. Past radio signatures 60
may or may not have a global position 90 assigned to them. However,
in all instances past radio signatures 60 have frequency windows 92
that exactly correspond to frequency windows 82 of current radio
signature 50. Thus, to save a current radio signature 50 as a past
radio signature 60, signal quality values 84 are simply mapped onto
and saved to the corresponding signal quality value 94 fields.
[0059] Step 204. Close to a transmitter, it is often the case that
the observed signal strength of the transmitter appears to be
saturated. For example, consider the case in which a radio receiver
reports an FM quality value in the range of 0 to 5 volts. Thus,
when receiver reports an FM quality value of five volts for a given
FM frequency, the frequency window that bounds the measured
frequency is flagged as saturated and is not used in subsequent
comparisons. While not intending to be limited to any particular
theory, the perceived saturation is likely due to limitations in
presently available radio signal decoders 12. While this perceived
saturation has no adverse affect on measured signature 50, little
information about the noise characteristics of the signal can be
gleaned at close distances to a transmitter. Thus, in some
embodiments, only non-saturated values from step 202 are
considered. In such embodiments, frequency windows 82 in which a
signal quality is saturated are removed from the radio signature.
For example, in some embodiments, this removal process entails
designating the saturated frequency window 82 for nonuse. Frequency
windows 82 that are designated for nonuse are not compared to
corresponding frequency windows 40 in radio signature lookup table
38 in subsequent processing steps.
[0060] Step 206. It has been observed that, for some radio signal
decoders 12, the signal quality value never falls to the lowest
possible value in the range of allowed values. In particular, it
has been observed that even at frequencies at which there is no
transmitter, a radio signal decoder 12 outputs a basal radio signal
quality voltage rather than outputting a reading of 0 volts. While
not intending to be limited to any particular theory, it is
believed that this basal voltage is caused by a DC offset in the
radio signal decoder 12. While such receiver limitations have no
known adverse affects on measured signature 50, they do not
contribute to the global position determination. Therefore, in some
embodiments, the current radio signature 50 is normalized by
removing the offset from each signal quality measurement 84 in
radio signature 50. The purpose of such normalization is to improve
the stability of subsequent comparison methods. In one embodiment,
signal quality 84 is FM quality and normalization 206 involves the
removal of an offset that appears in the FM quality signal.
[0061] In some embodiments, normalization 206 comprises amplifying
measured signal quality values to increase separation between data
peaks in the radio signature 50. Such amplification can be
accomplished by multiplying each signal quality 94 by a constant in
embodiments in which there is only a one signal quality 94
parameter measured per frequency window 92 (e.g., multiplication of
signal strength by a constant). While this has the effect of
amplifying noise in addition to true signals, it has been found
that such amplification increases the stability of the comparison
method by reducing its required sensitivity.
[0062] Methods for obtaining a current radio signature 50 have been
provided. It will be appreciated that the methods by which current
radio signature 50 were obtained can be used to measure each of the
radio signatures 39, typically at some time prior to execution of
steps 202 through 206. Such measurements are typically made by a
radio receiver that is coupled with a GPS system as described in
the exemplary systems below and/or some other mechanism for
determining global position. The radio receiver used to make the
measurements for radio signature 39 can be the same radio receiver
used to make the measurements for radio signature 50. However, in
more typical embodiments, different-radio receivers are used. Each
radio signature 39 can be processed to exclude saturated
frequencies and to normalize to remove any form of basal voltage in
the same manner in which radio signature 50 is optionally processed
in steps 204 and 206.
[0063] Step 208. In most instances, a comparison of the current
measured radio signature 50 to signatures 38 in lookup table 38 is
sufficient to uniquely identify the global position of radio
receiver 10. However, past radio signatures 60 can be used to break
any ties that may arise. For example, consider the case in which
radio receiver 10 is in a car heading North along a highway. At
time point one, a current radio signature 50 is measured.
Comparison of current radio signature 50 to each radio signature 39
in lookup table 38 identifies a clear best match, say radio
signature 39-1. Now, at point two, current radio signature 50 is
again measured. However, comparison of current radio signature 50
to each radio signature 39 in lookup table 38 identifies two radio
signatures 39 that match the new current radio signature 50. To
break the tie, the radio signature 39 in the set of two matching
radio signature 39 that is geographically proximate to the most
recent past radio signature (e.g., radio signature 60-1 FIG. 1B) is
selected. Selection of the geographically proximate radio signature
is selected on the premise that radio receiver 10 could not have
traversed too far between time step 1 and time step 2. This example
illustrates the use of a single past radio signature 60. However,
in practice, any number of past radio signatures can be used to
break ties.
[0064] Step 210. Once a current radio signature 50 has been
measured and optionally processed (e.g., saturated values removed
and the signature normalized), signature 50 is compared to one or
more radio signatures 39 in radio signature lookup table 38.
[0065] In some embodiments, a brute force approach is applied in
which a comparison score is generated for each such comparison. In
some embodiments this comparison score is simply an indication as
to whether the two signatures match. In one embodiment, a declining
threshold method is used. In the declining threshold method, the
frequency window 82 with the strongest signal quality 84 is first
considered. Only those respective radio signatures 39 that have a
measured signal in the corresponding frequency window 40 that is
stronger than the measured signal in any other frequency window of
the respective radio signature 39 are considered. For example,
consider the case in which a current radio signature 50 includes a
measured signal at frequencies 96.7, 98.5, and 100.3 and that the
signal for 96.7 is the strongest. Only those respective radio
signatures 39 that include a signal for 96.7 (or the frequency
window 40 that encompasses this signal) that is larger than any
other signal in the respective signature 39 are considered
candidates. If this comparison does not limit the candidate
signatures 39 to a single candidate signature, then the second
strongest signal in current radio signature 50 is considered and so
forth until a single candidate signature 39 is identified.
Comparison of just a single frequency in many instances is a
powerful indicator of the geographical location of radio signature
measurement model 30. Review of FM transmitter reference sources
registered with the Federal Communications Commission (FCC) in the
United States and the Canadian Radio-television and
Telecommunications Commission (CRTC) in Canada reveals that there
are relatively low upper bounds on the number of transmitters for
each FM frequency in Canada and the United States. That is, based
on a single frequency, the location of the receiver can be
determined to within less than 200 (maximum) locations within all
of Canada and the United States. Therefore, comparison of two,
three or four different frequencies using the above identified
declining threshold method is, in most instances, sufficient to
identify a single matching radio signature 39 in radio signature
lookup table 38.
[0066] In some embodiments, the signal strength of at least one
frequency is used to assign current radio signature 50 a global
location using the systems and methods of the present invention. In
more preferred embodiments, the signal strengths of two or more
frequencies are used to assign current radio signature 50 a global
location. In some embodiments, between two and ten frequencies are
used to assign current radio signature 50 a global location. In
some embodiments, between three and twenty frequencies are used to
assign current radio signature 50 a global location. In any of
these embodiments, one or more additional signal quality parameters
is optionally used to facilitate the assignment of a global
location to current radio signature 50.
[0067] In some embodiments, rather than the declining threshold
method, a "decision tree" approach is used to identify a match in
signature lookup table 38. In some embodiments of the "decision
tree" approach, the most powerful signals (frequencies or
corresponding frequency windows) in current radio signature 50 are
matched against candidate radio signatures 39 in signature lookup
table 38. Then candidate radio signatures 39 are assessed based on
the likeliness that such candidates represent the correct location.
For example, in cases where past radio signatures 60 with assigned
global positions 90 are available, candidate radio signatures 39
having global positions 62 that are proximate to assigned global
positions 90 are given more weight than distal signatures 39. This
process continues until a single geo-polygon target (radio
signature 39) is reached with the highest probability as the
solution. In some embodiments, other parameters in addition to
signal strength are used in the "decision tree" approach. For
example, in some embodiments, signal strength in addition to
available information about RDS signal quality is used. In fact,
any combination of signal quality 42 metrics that are stored in
memory 20 can be used.
[0068] In some embodiments, the signal quality metrics 84 measured
in the current radio signature are reduced to a searchable
expression. For example, consider the case in which current radio
signature 50 includes a measured signal at frequencies 96.7, 98.5,
and 100.3. This can be represented as an array that is zero
everywhere except for the three values in the array that represent
frequencies 96.7, 98.5, and 100.3. In alternative embodiments, the
three values respectively representing frequencies 96.7, 98.5, and
100.3 can be binary (e.g., be assigned the value "1"). In such
embodiments, the array can be represented as:
TABLE-US-00001 96.8 97.0 97.2 . . . 98.4 98.6 . . . 100.4 1 0 0 0 1
1
In this array, frequencies are assigned to frequency windows. For
example, the number 96.8 in the first row of the array represents
the frequency window spanning 96.6 to 96.8. Thus, 96.7 is placed in
this frequency window and assigned a value of "1." In some
embodiments, rather than assigning a first binary value (e.g., "1")
when a signal is observed, a value representative of signal
strength is provided (e.g., a real value between 0 and 5). Thus,
for example, in the case where 3.7 volts is measured for frequency
96.7, 4.2 volts is measured for frequency 98.5, and 2.4 volts is
measured for frequency 100.3, the array can be represented as:
TABLE-US-00002 96.8 97.0 97.2 . . . 98.4 98.6 . . . 100.4 3.7 0 0 0
4.2 2.4
In embodiments in which a real value is assigned, error tolerances
can be added. For example, consider the case in which the signal
strength for frequency 96.7 is 3.7 volts. An error value of, for
example, .+-.0.2 volts can be applied to the signal strength. Thus,
in an embodiment where an error value of .+-.0.2 volts is applied,
the array can be represented as
TABLE-US-00003 96.8 97.0 97.2 . . . 98.4 98.6 . . . 100.4 3.7 .+-.
0.2 0 0 0 4.2 .+-. 0.2 2.4 .+-. 0.2
In principle, in embodiments in which error bars are provided, the
present invention encompasses a broad range of possible error bars.
An example where a constant error is applied to all measured
signals has been illustrated above. In other examples, the error
bar for each measured signal is a function of the magnitude of the
measured signal. For example, consider the case where an error of
ten percent is allowed. In such an embodiment, the array can be
represented as:
TABLE-US-00004 96.8 97.0 97.2 . . . 98.4 98.6 . . . 100.4 3.7 .+-.
0.4 0 0 0 4.2 .+-. 0.4 2.4 .+-. 0.2
Upon review of the above disclosure, those of skill in relevant
arts will appreciate that there are many different error schemes
that could be applied in order to represent the signal quality of a
current radio signature 50 and all such schemes are within the
scope of the present invention. In practice, some calibration of
the error algorithm is needed in order to achieve a sufficient
probability that there is only one radio signature 39 in radio
signature lookup table 38 that matches a given current radio
signature 50.
[0069] In some embodiments, more than one type of signal quality
metric 84 can be found in the current radio signature 50 besides
signal strength as a function of signal frequency. In general, such
additional signal quality metrics 84 can be divided into two
categories: (i) those that have been measured as a function of
frequency (e.g. RDS signal quality) and (ii) those in which only a
single value is measured for the entire frequency spectrum under
consideration. Each metric in the former class of additional signal
quality metrics can be assigned an additional row in the arrays
illustrated above whereas each metric in the latter class of
additional signal quality metrics can simply be added as another
column to the arrays described above.
[0070] The signal quality metrics 42 of radio signatures 39 can be
represented in an array format just like the signal quality metrics
84 of current radio signature 50. In fact, in some embodiments,
error bars are applied to signal qualities 42 (the reference signal
qualities of FIG. 1A) rather than signal qualities 84 (the measured
signal qualities of FIG. 1B). This is because the reference signal
qualities can be measured at a given global position 62 using more
sensitive equipment, different types of equipment (e.g., different
antenna configurations) or under various different conditions (time
of day, time of year, weather, etc.) in order to obtain a realistic
determination in the variance in signal quality 42 across such
conditions. This variance can then be formulated into specific
error values for each signal quality value. As an example, consider
the case in which frequencies 96.7, 98.5, and 100.3 are measured at
a given global position 62. In constructing a radio signature 39
for this global position 62, frequencies 96.7, 98.5, and 100.3 can
be measured at global position 62 at different times of day, under
different weather conditions, with different radio signal decoders
12 and/or different antenna configurations. Suppose that when this
is done, it is found that the signal strength for frequency 96.7
has a signal strength of 3.0.+-.0.4 volts whereas the signal
strength for frequency 98.5 has a signal strength of 3.0.+-.0.001
volt. In this case, frequency 96.7 will be assigned a much larger
error bar in the corresponding radio signature 39 than frequency
98.5.
[0071] The arrays described above can then be compared using any of
a wide range of comparison techniques. For example, the strongest
signals in current radio signature 50 can be compared first in the
declining threshold or decision tree approaches, etc. However, the
representation of current radio signature 50 in the array format
shown above (and the description of radio signature 39 having the
same format) is meant to aid in the visualization of what data is
used to identify a matching radio signature 39 in radio signature
lookup table 38. In practice, it is not necessary to represent
signal quality metrics 84 (or signal quality metrics 42) in the
array format described above in order to find matching radio
signatures 39.
[0072] In some embodiments, enough quality metrics are used and
radio signature lookup table 38 is sufficiently populated with
radio signatures 39 to ensure that radio receiver 10 is localized
to a specific global position. In some embodiments in which this is
the case, radio signature lookup table 38 is arranged as a tree.
For example, in some embodiments, radio signatures 39 are organized
into a tree in which parent nodes representing certain radio
signatures 39 point to daughter nodes representing radio signatures
39 that are geographically proximate to the signatures represented
by parent nodes and/or have a signature that is similar to the
signatures represented by parent nodes. There are several trees
data structures known in the art and any such tree data structure
can be used to organize radio signature lookup table 38.
Representative examples include, but are not limited to, binary
trees, red-black trees, splay trees, and B-trees. See, for example,
Binstock and Rex, 1995, Practical Algorithms for Programmers, pp.
245-231, Addison Wesley, Reading Mass.; Adel'son-Vel'skii and
Landis, 1962, "An algorithm for the Organization of Information,"
Soviet Math 3, pp. 1259-1263; Bayer and McCreight, 1972,
"Organization and Maintenance of Large Ordered Indexes," Acta
Informatica 1, pp. 173-189; Corner, 1979, "The Ubiquitous B-tree,"
Computing Surveys, Vol. II, pp. 121-137; Knuth, 1973, the Art of
Computer Programming, Vol. 3: Sorting and Searching, Addison
Wesley, Reading Mass.; Melhorn, 1984, Data Structures and
Algorithms I: Sorting and Searching, Springer-Verlag, Berlin,
Germany; Sleator and Taijan, 1985, "Self-Adjusting Binary Search
Trees," Journal ACM 32, pp. 652-686; Taijan and Van Wyk, 1988, "An
O(n log log n)-Time Algorithm for Triangulating a Simple Polygon,"
Siam J. Comput 17, pp. 143-178, each of which is hereby
incorporated by reference in its entirety.
[0073] In some embodiments in which enough quality metrics are used
and radio signature lookup table 38 is sufficiently populated with
radio signatures 39 to ensure that radio receiver 10 is localized
to a specific global position, radio signature lookup table 38 is
encoded as a hash table. In such embodiments the quality metrics
(quality metrics 42 in the case of radio signatures 39; quality
metrics 84 in the case of measured radio signature
[0074] 50) are used as input to a common hash function. In such
embodiments, a search for a match between measured ratio signature
50 and a radio signature 39 is implemented as a hash table lookup.
Hashing is a well known algorithm. For exemplary hashing techniques
that can be used in accordance with the present invention see, for
example, Binstock and Rex, 1995, Practical Algorithms for
Programmers, pp. 63-93, Addison Wesley, Reading Mass.; Aho et al.,
1986, Compilers: Principles, Techniques, and Tools, Addison-Wesley,
Reading, Mass.; Holub, 1990, Compiler Design in C, Prentice Hall,
Englewood Cliffs, N.J.; Kruse et al.; 1991, Data Structures and
Program Design in C, Prentice Hall, N.J.; and UNIX Press, 1990,
System V Application Binary Interface--Unix System, Prentice Hall,
Englewood Cliffs, N.J., each of which is hereby incorporated by
reference in its entirety.
[0075] Step 212. In step 212, a global position 80 is assigned to
radio receiver 10 based on the respective radio signature 39 in
radio signature lookup table 38 that best matches current radio
signature 50 as determined by step 210. In cases where a plurality
of hits (plurality of candidate radio signatures 39) are found in
step 210 rather than a unique match, previously measured radio
signatures 60 can be used to identify the appropriate radio
signature among the candidates. For instance, those candidate radio
signature that represent global positions most proximate to the
global positions identified for previously measured radio
signatures 60 can be upweighted.
[0076] In some embodiments global position 80 is localized in step
212 to a geometric polygon that encompasses 50 contiguous square
miles or less. In more preferred embodiments, global position 80 is
localized in step 212 to a geometric polygon that encompasses 5
contiguous square miles or less. In still more preferred
embodiments, global position 80 is localized in step 212 to a
geometric polygon that encompasses 1 contiguous square mile or
less. In still more preferred embodiments, global position 80 is
localized in step 212 to a geometric polygon that encompasses 0.5
contiguous square miles or less. In still more preferred
embodiments, global position 80 is localized in step 212 to a
geometric polygon that encompasses five contiguous acres or less.
In still more preferred embodiments, global position 80 is
localized in step 212 to a geometric polygon that encompasses one
acre or less. In some embodiments, global position 80 is localized
in step 212 to within twenty-five, twenty, ten, or five contiguous
city blocks of the actual location of radio receiver 10.
[0077] In some embodiments, a comparison of the global position 80
identified in step 212 to the global positions 90 assigned in past
radio signatures 60 is used to determine whether radio receiver 10
is moving and, if so, the direction radio receiver 10 is moving.
For example, consider the case in which step 212 determines that
radio receiver is at global position 1. And past radio signature
60-1 reports a global position 2. Suppose that position 2 is
directly South of position 1. This indicates that between the
current measurement and the last measurement, radio receiver 10 has
moved directly North. In some embodiments, the current radio
signature 50 is polled sufficiently frequently and global positions
assigned to the radio signatures are sufficiently precise to
establish not only the direction that radio receiver 10 is
traveling, but also the speed at which the receiver is
traveling.
[0078] Step 214. In typical embodiments, steps 202-212 are
performed by radio signature comparison module 32. As such, by the
time step 214 is reached, an accurate determination of the global
position of radio receiver 10 has been accomplished without any
need for a conventional satellite global positioning feed. All that
is needed is a program radio signal decoder 12 and programmable
circuitry that can search a radio signal lookup table 38 for
matching radio signatures 39. Furthermore, in some embodiments, the
direction and even the speed at which radio receiver 10 is moving
can be determined.
[0079] In step 214, the information obtained using the novel
methods of the present invention is used for any of a number of
purposes. For example, in some embodiments, newly assigned global
position 80 is displayed on display 16. In some embodiments,
processing step 214 is accomplished by radio display module 34. In
some embodiments, radio display module 34 and radio signature
comparison module are part of a common software module.
[0080] In some embodiments, step 214 comprises using newly assigned
global position 80 to perform a table lookup in optional radio
display table 70. Radio display table 70 includes data records 72
for select global positions. To illustrate, consider the case in
which global position 80 is geographic position 1012. In step 214,
a determination is made as to whether radio display table 70
includes a record 72 for geographical position 1012. When this is
the case, radio display module 34 optionally displays all or a
portion of the contents of the corresponding record on display 16.
In some embodiments information 72 includes information not only
for display 16 but also audible information, such as an alarm, a
sound, an audible message, audible instructions, a song, etc. In
such instances, the audible information is sounded using the
amplification system (not shown) of radio receiver 10.
[0081] In some embodiments, information 72 is updated by table
update module 36 on a regular or irregular basis using information
received by radio signal decoder 10. For example, in some
embodiments radio signal decoder 10 receives a Radio Data System
(RDS) or high definition (HD) signal that carries geographic
specific traffic, weather, or general news updates. Table update
module 36 parses this information into appropriate records 72.
Then, in step 214, this information is displayed on display 16
and/or audibly sounded.
5.4 Specific Comparison Method
[0082] An overview of systems and methods for pinpointing the
geographic position of a radio receiver using radio signals has
been provided in conjunction with FIGS. 1 and 2. Central to such
systems and methods is a process for matching signal quality
metrics 84 of a current radio signature 50 to signal quality
metrics 42 of a plurality of radio signatures 39. This comparison
is embodied as step 210 in FIG. 2. FIG. 3 shows one detailed way of
implementing step 210 of FIG. 2.
[0083] Step 302. In step 302, a variable N is set to one.
[0084] Step 304. In step 304, the N.sup.th largest signal 84 in
current radio signature 50 is selected.
[0085] Step 306. In step 306, radio signature 50 is compared to
radio signatures 39 in radio signature lookup table 38. Radio
signatures 39 are eliminated from further consideration if they do
not have a signal 42 at the same frequency (or frequency window) as
the frequency of the N.sup.th largest signal selected in step 304.
Moreover, in some embodiments, radio signatures 39 are eliminated
from further consideration if they do not have a corresponding
signal 42 with the same relative magnitude as the N.sup.th largest
signal 84 selected in step 304. To illustrate, consider the case in
which the N.sup.th largest signal 84 selected in step 304 has a
frequency of 96.7. Each respective radio signatures 39 that does
not have a frequency window 40 encompassing the frequency 96.7 in
which the corresponding signal quality 42 is higher than the signal
quality 42 of any other frequency window 40 in the respective radio
signature 39 is eliminated from further consideration.
[0086] Step 308. In step 380 a determination is made as to whether
elimination step 306 has eliminated so many radio signatures 39
from consideration that there is now only one possible signature 39
remaining in lookup table 38. When such a determination is
affirmative (308-Yes), process control passes to step 310. When
such a determination is not affirmative (308-No), process control
passes on to step 312.
[0087] Step 310. Step 310 is reached if a unique radio signature 39
has been identified as matching current radio signature 50. In such
instances, global position 80 is assigned the value of the global
position 62 of the matching unique radio signature 39 and the
process is terminated.
[0088] Step 312. Step 312 is reached when a unique radio signature
39 has not been identified. In step 312, a determination is made as
to whether there are remaining peaks (frequencies) in current radio
signature 50. If so, process control passes to step 314. If no
peaks in current radio signature 50 remain, process control either
terminates unsuccessfully (not shown) or passes on to step 316.
[0089] Step 314. In step 314 counter N is incremented by "1",
indicating that the next most significant peak in radio signature
50 is to be selected for evaluation. Then, process control returns
to step 304 where the N.sup.th largest peak in current radio
signature 50 is selected for evaluation. Process control then
proceeds once again to step 306. In step 306 those radio signatures
39 that do not have the N.sup.th largest peak registered as the
N.sup.th largest peak are eliminated. To illustrate, consider the
case in which the N.sup.th largest signal 84 selected in the first
instance of step 304 has a frequency of 96.7. Each respective radio
signatures 39 that does not have a frequency window 40 encompassing
the frequency 96.7 in which the corresponding signal quality 42 is
higher than the signal quality 42 of any other frequency window 40
in the respective radio signature 39 is eliminated from further
consideration. However, this was not sufficient to uniquely match a
radio signature 39 to radio signature 50. Suppose that five radio
signatures 39 in radio signature lookup table 38 remained after the
first instance of elimination process 306. Thus, a second instance
of step 304 is run in which the second largest peak is selected.
Suppose that the second largest frequency is 98.5. In the second
instance of elimination process 306, each respective radio
signatures 39 in the set of five remaining radio signature 39 that
do not have a frequency window 40 encompassing the frequency 98.5
in which the corresponding signal quality 42 is the second highest
signal quality 42 in the respective radio signature 39 is
eliminated from further consideration. The loop defined by
processing steps 304 through 314 continues until there is only a
single radio signature remaining or there are no further peaks in
radio signature 50 to analyze.
[0090] Step 316. In some embodiments, the geographic positions
assigned to past radio signatures 60 are used to help eliminate
candidate radio signatures 39. For instance, if there are two
candidate radio signatures 39 remaining and one of the two
signatures is proximate to the geographic positions assigned to
past radio signatures 60 and the other is not, the proximate
signature 39 is selected and the other signature is eliminated.
5.5 Population of Radio Signature Lookup Table 38
[0091] The present invention uses efficient, reliable means for
populating radio signature lookup table 38. Such techniques can be
classified into three types of models (i) fully predictive, (ii)
fully empirical ("brute-force"), and (iii) empirical-predictive
hybrid. As waves travel from a transmit antenna to a receive
antenna, they suffer attenuation due to propagation loss. Fully
predictive models predict signal strengths based on known
transmitter locations and attenuation models. In contrast, fully
empirical models rely on reference measurements of signal strengths
taken from known reference locations throughout a supported
geographic region. In the empirical-predictive hybrid approach,
empirical data is used to verify and/or calibrate a predictive
model.
[0092] 5.5.1 Fully predictive models. Radio propagation in land
mobile environments is subjected to degradation due to the
combination of three main effects: (i) large scale path loss (area
mean variation), (ii) large scale shadowing (local mean variation),
(iii) and small scale multi-path fading (instantaneous
variation).
[0093] The large scale path loss, or area mean variation, is caused
by signal attenuation due to the distance between transmitter and
receiver and its variation follows the inverse of the n.sup.th
power of this distance, where n is commonly referred to as the path
loss exponent. The value of n typically lies between 2 and 5. A
value of 2 refers to free space propagation in which the variation
of the received signal follows the Friis formula. See de P. Rolim,
Telecomunicacoes 4, December 2001, pp. 51-55; and Rappaport,
"Wireless Communications--Principles and Practice," IEEE Press,
Inc., New York and Prentice Hall, Inc., N.J., 1996, each of which
is incorporated by reference in its entirety. A value greater than
2 indicates the influence of structures on the earth surface. Dense
urban environments always have values of n on the order of 4 or
even 5. Suburban ones have n ranging from 2 to 4.
[0094] Large scale shadowing is caused by the terrain contour and
other obstructions between the transmitter and receiver, in the
local sense. It corresponds to variations about the area mean value
and typically follows a log-normal probability density independent
of the distance between transmitter and receiver.
[0095] Small scale multi-path fading has to do with the fact that
signals received by a mobile terminal come from an infinitely large
number of propagation paths. These multiple propagation paths are
caused by reflection, diffraction and/or scattering of the radio
wave in natural structures (hills, vegetation, etc.) and in
human-made structures (buildings, poles, etc.). The composite
signal at the receiver antenna suffers magnitude and phase
variations due to the multiple propagation paths that interfere
with each other constructively and destructively, depending on the
spatial position of the receiver. These variations are termed
multi-path fading and they occur at a rate that depends directly on
the speed of motion of the receiver and/or of the objects around
the receiver.
[0096] Thus, propagation mechanisms are very complex and diverse.
First, because of the separation between the receiver and the
transmitter, attenuation of the signal strength occurs. In
addition, the signal propagates by means of complex phenomena such
as diffraction, scattering, reflection, transmission, refraction,
etc. A propagation model is a set of mathematical expressions,
diagrams, and algorithms used to represent the radio
characteristics of a given environment. In the present invention,
they are used to generate geopolygons (radio signatures 39) based
on the intersections of transmitter broadcast areas and compensates
for signal attenuation that arises, inter alai, as a result of one
or more of the factors discussed above. Table 1 provides exemplary
propagation models that can be used to facilitate such
calculations. However, it will be appreciated that the present
invention is not limited to the use of these models.
TABLE-US-00005 TABLE I Exemplary propagation models used to
calculate signal quality 42 for radio signatures 39. Operating
Frequency Range Terrain Terrain Propagation Model (MHz) (km)
Elevation Type Free Space Unlimited Unlimited Not applicable Not
applicable Rec. ITU-R P.370-7 30-250 0-1000 Yes Some 450-1000 Rec.
ITU-R P.1146 1000-3000 0-500 Yes Some Okumura Hata 150-1500 0-20
Not applicable Some CRC-PREDICT 30-3000 Unlimited Yes Yes v.2.07
CRC-PREDICT 30-3000 Unlimited Yes Yes v.2.08r2 CRC-PREDICT 30-3000
Unlimited Yes Yes v.3.21 Longley Rice 20-20000 1-2000 Yes No TIREM
20-20000 Unlimited Yes No Egli Unlimited Unlimited Not applicable
Not applicable
While most of these models can provide a fairly accurate
representation of the desired geographic discretization, more
accurate propagation models lead to more accurate signal quality
parameters 42 in table update module 36. The CRC-PREDICT model
(e.g., CRC-PREDICT v.2.08r2) takes into account terrain and clutter
effects. Because of this, it reportedly produces more accurate
results than the other propagation models (e.g., five dB standard
deviation with sufficient map data). In addition to accuracy
advantages, a fully predictive model is attractive because of the
relatively low overhead (compared to the "brute-force" method) in
development and maintenance time, the possibility for inclusion of
calibration data in the signature database itself, and the
geographic completeness possible. Because predictive models involve
irregular geographic regions, an efficient means of geo-referencing
the transmitter locations and broadcast regions is desirable, and a
means of geo-encoding transmitted data for dissemination by region
is also desired.
[0097] 5.5.1.1 Free space propagation model. The free space
propagation model assumes the ideal propagation condition that
there is only one clear line-of-sight path between the transmitter
and receiver. As such, in the absence of any reflections or
multipaths, radio wave propagation can be modeled using the free
space propagation model which says:
S r = S t G t G r ( .lamda. 4 .pi. d ) 2 ##EQU00001##
where, [0098] S.sub.t is Received Power in Watts [0099] S.sub.t is
Transmitted Power in Watts [0100] G.sub.t is Transmit Antenna Gain
(isotropic) [0101] G.sub.r is Receive Antenna Gain (isotropic)
[0102] .lamda. is Wavelength [0103] d is T.sub.x/R.sub.x Separation
in the same units as wavelength The equation can be expressed in dB
units by taking the logarithm (log.sub.10) of both sides to
obtain:
[0103] S r ( dBW ) = S t ( dBW ) + G t ( dBi ) + G r ( dBi ) + 20
log 10 ( .lamda. 4 .pi. ) - 20 log 10 ( d ) ##EQU00002##
The last two terms of this equation combined are called Path Loss
(PL) for free space propagation. This is the channel's loss in
going from the transmitter to the receiver expressed in decibels.
The first two right hand terms combined is called Effective
Isotropic Radiated Power or EIRP. EIRP is the equivalent
transmitter power required if an isotropic (0 dBi) antenna were
used. Using these definitions the following equation is obtained
where, for free space propagation; PL (dB)=-20
log.sub.10(1/4pd):
S.sub.r=(dBW)=EIRP(dBW)+G.sub.r(dBi)-PL(dB)
For non free space propagation conditions, PL might be described by
PL=A+B log.sub.10 (R). For more information on the free space
propagation model see Friis, "A note on a simple transmission
formula," Proc. IRE, 34, 1946; and U.S. Pat. Nos. 6,700,902;
6,542,719; and 6,360,079, which are hereby incorporated by
reference in their entireties.
[0104] 5.5.1.2 Other exemplary predictive propagation models. Rec.
ITU-R P.370-7 and Rec. ITU-R P.1146, which are hereby incorporated
by reference in their entireties, are recommendations promulgated
by the International Telecommunications Union and can be ordered
from the URL http://www.itu.int/publications/itu-r/. The Okumaru
Hata propagation model is described in the article Okumura et al.,
1968, "Field Strength and Its Variability in VHF and UHF
Land-Mobile Radio Service," Review of the Electrical Communications
Laboratory 16, Nos. 9-10, which is hereby incorporated by reference
in its entirety.
[0105] CRC-PREDICT (e.g., CRC-PREDICT v.2.07, CRC-PREDICT v.2.08r2,
and CRC-PREDICT v.3.21) is used for estimating radio signal
strengths on terrestrial paths at VHF and UHF, given a transmitter
location, power, and a receiver location. Since transmission paths
are often obstructed by terrain, CRC-PREDICT can operate
concurrently with a machine-readable topographic database
consisting of elevation and surface codes; recorded at regular
intervals (e.g. 500 meter intervals). CRC-PREDICT can also be used
without such a database, either by manually entering path profiles
or by using a general description of the terrain. When a path
profile is present, the main calculation is that of diffraction
attenuation due to terrain obstacles. These obstacles are primarily
hills, or the curvature of the earth, but can also include trees
and/or buildings. The presence and particular location of trees and
buildings are considered in the calculation. However, their height
and structure are not considered. The diffraction calculation is
done by starting at the transmitting antenna and finding the radio
field at progressively greater distances. At each step, the field
at a point is found by a numerical integration over the field
values found in the previous step. For long paths, tropospheric
scatter becomes important. CRC-Predict combines the tropospheric
scatter signal with the diffraction signal. For more information on
CRC-Predict, see "Review of the Radio Science Branch of the
Communications Research Centre Canada--Final Report," Performance
Management Network Inc., March 2001 which can be found at the URL
http://www.ic.gc.ca/cmb/welcomeic.nsf/vRTF/AuditJan2004E/$file/RadioScien-
ceReview FinalReport.pdf and is hereby incorporated by reference in
its entirety.
[0106] The Longley-Rice error propagation algorithm is reported in
Longley and Rice, July 1968, "Prediction of Tropospheric radio
transmission over irregular terrain, A Computer method-1968," ESSA
Tech. Rep. ERL 79-ITS 67, U.S. Government Printing Office,
Washington, D.C., which is hereby incorporated by reference in its
entirety. The Terrain Integrated Rough Earth Model (TIREM) is
described in IEEE Vehic. Tec. Society, Special Issue on Mobile
Radio Prop., IEEE Trans. Vehic. Tech., vol. 37, 1988, pp. 3-72,
which is hereby incorporated by reference in its entirety. The Egli
error propagation model is described in "Radio Propagation Above
40MC Over Irregular Terrain," Proceedings of the IRE, Vol. 45, Oct.
1957, pp. 1383-1391, which is hereby incorporated by reference in
its entirety. Additional propagation models that can be used to
populate table update module 36 include the Carey model from FCC
Report No. R-6406, "Technical Factors affecting the assignment of
facilities in the domestic public land mobile radio service," by
Roger B. Carey, Jun. 24, 1964, and Part 22 of the FCC Rules; the
Bullington model from "Radio Propagation for Vehicular
Communications," by Kenneth Bullington, IEEE Transactions on
Vehicular Technology, Vol. VT-26, No. 4, November 1977; the
Hata/Davidson model from "A Report on Technology Independent
Methodology for the Modeling, Simulation and Empirical Verification
of Wireless Communications System Performance in Noise and
Interference Limited Systems Operating on Frequencies between 30
and 1500 MHz," TIA TR8 Working Group, IEEE Vehicular Technology
Society Propagation Committee, May 1997; the Rounded Obstacle model
from Section 7 "Diffraction Over a Single Isolated Obstacle" and
Section 9 "Forward Scatter" of Tech Note 101 ("Transmission Loss
Predictions for Tropospheric Communication Circuits", 1967, NTIS)
and the National Radio Astronomy Observatory QZGBT program, each of
which is incorporated by reference in its entirety. Additional
discourse on error propagation models, including the physics
considered in such models, is found in Neskovi et al., "Modern
Approaches in Modeling of Mobile Radio Systems Propagation
Environment," IEEE Communications Surveys, Third Quarter 2000,
which is hereby incorporated by reference in its entirety.
[0107] 5.5.1.3 Input data for error propagation models. Many of the
error propagation models that can be used in the present invention
work in conjunction with information on terrain (hills, elevation,
etc.) There are numerous sources for such terrain data including,
but not limited to, the United States Geological Survey
(http://edc.usgs.gov/geodata/) for United States map data and the
Ministry of Natural Resources for Canadian map data. Such
information is available through distributors such as GEOREF
Systems Ltd. (http://www.georef.com/", and GeoBase Ltd.
(http://www.geobase.ca/).
[0108] Furthermore, such error propagation models require the
location of transmitters. FM transmitter reference sources include
official registration bodies such as the Federal Communications
Commission (FCC) (Washington, D.C.) and the Canadian
Radio-television and Telecommunications Commission (Ottawa,
Ontario). Data obtained from these sources is preferably verified
both with commercially available information, station engineers and
with actual field measurements. FCC FM transmitter information can
be accessed by commercially available databases and/or cooperation
agreements with companies such as Navteq (Chicago, Ill.). Navteq
provides digital map information and related software and services
used in a variety of navigation, mapping and geographic-related
applications.
[0109] 5.5.2 Empirical models. Empirical models compare current
radio signature 50 to radio signatures 39 measured at predetermined
locations using the techniques described above in conjunction with
FIGS. 1 through 3. Typically, the use of empirical models is unable
to match exact signatures. Rather, the approach determines the
"closest match," thus giving an approximate location within
acceptable error bounds.
[0110] For the empirical model to be useful, a large set of
measured data is produced so that an accurate reflection of all
geographies in the eNav application area is available. This model
lacks the geographic completeness of the predictive model. However,
for smaller geographies (e.g. a state, a city, or town) it can
provide comprehensive support. Since the empirical approach will
generate a database of known "real" signatures, terrain and clutter
calibration, if any, is done at the sensing end of the system
(in-vehicle) before signature comparison is possible. A possible
advantage of the empirical approach is the potential regularity of
the geographic regions encompassed by each radio signature 39. With
a predictive model, broadcast areas may be irregular and small
anomalous regions can be created by irregular terrain. The
irregularity of the regions and the possibility for many smaller
regions with distinct signatures might require much more complex
encoding and decoding methods for the dissemination of
location-sensitive information. The possibility of regularly spaced
regions using an empirical model is more conducive to efficient and
simple encoding schemes. It should also be noted that an empirical
model does not require knowledge of transmitter locations or
broadcast areas. This does not mean that transmitter changes will
not affect the system. On the contrary, an empirical model of this
nature requires significant resources to accurately maintain, as
updates to table update model 36 (under the empirical approach)
will require both man power and travel time.
5.6 Exemplary System
[0111] To test the methods of the present invention, an exemplary
system was built. The system includes a generic RDS radio receiver
FM Module, implemented on a breadboard (e.g., a Wish board no.
204-1). This fully integrated FM module provides a way to access an
analog FM quality reading (as well as a multipath rating and RDS
quality reading) at any given frequency. The FM quality signal is
used as a good indicator of field/signal strength (signal quality
42 FIG. 1A) across the FM frequency band at any given position. The
module is also flexible in that it provides electronic tuning and
parameter control through an I2C interface (which can be accessed
by the laptop through an interface board on the printer port). A
circuit diagram of this breadboard is shown in FIG. 4. The generic
RDS radio receiver requires very little external hardware for
implementation, but power was supplied by a 12 volt Compaq power
supply (Series PS2022). One other external in the exemplary system
is an FM band antenna that is of the simple automotive whip type.
The case of a PC was used to as a mounting point for all of the
other equipment, such as the breadboard and the Weidmuller terminal
block, in the exemplary system. The Weidmuller terminal block
provides a physically sturdy connection for the analog outputs of
the radio receiver to the data capture unit. The data capture unit
resides in a 12 bit 250 Ksps, 16 channel ADC Elan Digital Systems
(Segensworth West, Fareham, United Kingdom) AD132 DAQ PCMCIA card
that is installed in slot one of a Dell (Austin Tex.) PPI Inspiron
7500 personal computer. The analog-to-digital capabilities of this
card are used to record the FM Quality, Multipath output and RDS
Quality signals from the radio receiver, all of which originate
from the radio receiver as voltages in the range of zero to five
volts. After conversion, all the digital values are both displayed
on the laptop graphical interface and stored on the hard drive.
[0112] In order to provide a baseline or context from which to
develop a model, a Garmin GPS unit 35-USB (Garmin International
Inc., Olathe, Kans.) was used to gather the various positional and
velocity coordinates and the accurate time when the analog readings
are taken. This unit provides approximately 10-meter accuracy
without correction, which is more than sufficient for the
granularity of the exemplary system. The GPS coordinates and time
are stored with the analog reading values on the laptop hard drive.
The GPS unit communicates with and is powered by the USB interface.
A system diagram of this setup is illustrated in FIG. 5.
[0113] A variety of software modules were run on the laptop
computer in order to collect the desired date. One low level
software module was an I2C control module. The I2C control module
provides the ability to set values on the RDS radio receiver
through the I2C interface board. The I2C interface board was
obtained from demoboard.com. The I2C board allows the I2C control
module software to electronically tune the radio receiver to any
given frequency in the FM band. The I2C board and corresponding
control module also provide access to FM demodulation parameters
used inside the radio receiver. Such parameters could be used as
additional signal quality characteristics 42.
[0114] Another software module installed on the laptop computer is
a data capture module. The data capture module interfaces with the
AD132 PCMCIA at the Windows DLL level to allow for configurable
sample rate and sampling time (which taken together give a fixed
number of samples). Although other values could be used, the
internal settings were set to sweep at 1000 samples/second for a
length of one second per FM frequency. The data capture includes
routines to perform evenly weighted averages and output the average
value to higher-level modules. The process is adaptable to multiple
inputs and is set by default for three analog inputs.
[0115] Another low level software module implemented on the laptop
computer is a GPS Unit Interface Module. The GPS unit interface
module decodes a serial stream provided by the USB-to-Serial driver
into geo-position variables like latitude, longitude, speed,
heading and time, placing them in internal variables for display
and data-logging. Analog readings that are taken by the Data
Capture Module are related back to reality by combining them with a
position and time. The GPS values provide this baseline. A
limitation of this experimental system is that updates are only
available from the hardware every second. Because the experimental
model's granularity in time and position will be much larger, this
did not affect results significantly.
[0116] In addition to the low level modules, higher level modules
were also implemented on the lap top computer. Such modules
included a data logging module. Given any set of internal variables
(which is completely configurable) this module will log those data
values to a comma-separated file each time a trigger is activated.
Internally, this occurs after the GPS position and time are
collected and the analog values are recorded for the current FM
frequency. It also provides the facility to give a "name tag" to
the current GPS location and log it to a separate file for later
reference. Another high level interface was a user interface module
providing a graphical user interface (GUI) to the other modules in
the system. The GUI displays current values of all internal
variables of the program (GPS, analog readings, and FM frequency).
The GUI can configure which list of FM frequencies to sweep and
change the target log file. It has the ability to produce
independent geo-code/time tags with text descriptions with button
click. Controls are available to start and stop the automatic
frequency sweep/data-capture process or to generate FM quality,
multipath and RDS quality readings at one specific frequency. A
screenshot of this exemplary GUI is illustrated in FIG. 6.
5.7 Signature Uniqueness
[0117] A preliminary signature uniqueness study was conducted using
transmitter registration data and the equipment described above and
depicted in FIGS. 4-6. It was found that, in Canada and the United
States, the majority of signatures containing more than a single FM
signal (that is, more than one transmitted frequency), are unique.
In fact, of all signatures that have more than a single signal,
there are, at most, three cities that have the same signature. It
should be noted that this is not an exhaustive uniqueness study for
several reasons. First, transmitter locations do not necessarily
correspond to registration cities. Second, the signature at any
given location often depends on transmitters in surrounding cities
as well as the current one. That is, broadcast areas do not
correspond to city boundaries). Third, the signature within a given
city can vary due to low power transmitters (e.g., with broadcast
areas smaller than the city boundaries) and due to terrain and
clutter effects (e.g., there can be more than one signature per
city).
[0118] Another important observation that can be made based on this
registration data is that, regardless of the correspondence between
transmitter locations and city boundaries, there are relatively low
upper bounds on the number of transmitters for each frequency in
Canada and the United States. That is, based on a single frequency,
the location of the receiver can be determined to within less than
200 (maximum) possible locations within all of Canada and the
United States. These findings provide clear support for the systems
and methods of the present invention.
5.8 Experimental Model Development
[0119] Several drive tests in the Waterloo area were used to
determine whether or not generating baseline data for an empirical
model was viable. The measured signature for a moving drive test in
and around a portion of the Waterloo area is shown in FIG. 7 before
normalization and in FIG. 8 after normalization. The figure shows
the approximate variation of the various FM frequencies within the
target area, indicating that of a sensed FM signature with signal
peaks at 96.7, 98.5, 100.3, and 105.3 should correspond to this
geographic region. To verify this, a comparison to transmitter
registration data was done. While there are 110 cities with
transmitters for 96.7, 81 cities with transmitters for 98.5, and 89
cities with transmitters for 105.3 (see FIG. 9), there is only one
city with all three frequencies: Kitchener, Ontario. The presence
of 100.3 effectively subdivides the broadcast regions for the
Kitchener-based transmitters, as there is only a signal for this
frequency in a portion of the test locations. It turns out that the
transmitter for this frequency is a low power transmitter used for
the University of Waterloo radio station. Thus, within the
broadcast area of the Kitchener-based transmitters, only those
areas within a certain distance of the University of Waterloo would
yield FM signatures that include 100.3 FM. This is clear evidence
that the systems and methods of the present invention can uniquely
determine receiver location with a granularity smaller than a
single broadcast region. This drive test also indicates that the
systems and methods of the present invention will function using an
empirical model by comparing sensed FM signatures to baseline data
(such as the data collected for the Waterloo region). The use of
empirical model such as that described in this example is only
practical in small target areas. For larger areas, predictive
models are preferable.
5.9 Signature Comparison
[0120] A declining threshold method can be used with either an
empirical model or a predictive model, as not all sources of error
can be accounted for in either model. Using a declining threshold
method on the data obtained from the Waterloo drive test yields a
set of comparisons. First 98.5 and 105.3 are considered, because
they are the maximum peaks. Already this places the receiver in a
limited number of regions. As the threshold declines, 100.3 may or
may not be considered depending on how close the receiver is to the
University of Waterloo. The inclusion of 100.3 places the receiver
in the Waterloo/Kitchener region. Already, by considering three
peak frequencies, the receiver position has been uniquely
determined. If the frequency 100.3 is not included in the
signature, then 96.7 is the next peak to cross the declining
threshold. Use of the frequencies 96.7, 98.5, and 105.3, places the
receiver within the Kitchener broadcast region. As the threshold
continues to decline, the additional peaks of 88.3, 89.9, 91.5,
92.1, and 95.3 place the receiver in a subsection of the Kitchener
broadcast area where these signals can be sensed.
[0121] At this point it should be noted that 98.7 and the multitude
of signals in the higher portion of the FM band (above 102.5) were
not considered in the declining threshold method. The higher
portion of the FM band was not included in the declining threshold
method because none of the frequencies (with the exception of
105.3, which was included in the comparison) are obvious peaks
above their neighboring frequencies. This illustrates the point
that the declining threshold method of comparison only considers
peak data. While the signature in FIG. 8 is locally normalized,
only the global FM floor (that is, the floor common to all
frequencies in the FM band) is removed in order to produce this
normalization. A better method of normalization, such as a
windowing method, would be more useful for differentiating between
strong signals and signal peaks.
5.10 Sources of Noise
[0122] Several sources of noise affect the FM signature sensed by a
receiver. To isolate the various kinds of noise, several targeted
drive tests were conducted. First, a test run was performed from
Waterloo to Toronto by measuring a few select frequencies for which
there is decent signal reception while on route from Waterloo to
Toronto. The results of these measurements are shown in FIGS. 10
and 11, with signal strength plotted against distance from the
transmitter (using a J2 elliptical model for the Earth to calculate
the absolute distance between the transmitter and receiver based on
recorded GPS coordinates). These figures illustrate several
important trends. Close to the transmitter, the recorded signal
levels appear to be saturated, most likely due to limitations in
the test hardware (representative of limitations that might be
present in production receivers). While this has no ill effect on
the FM signature at these locations, very little information about
the noise characteristics of the signal can be gleaned at these
distances. FIGS. 10 and 11 also illustrate the general trend of the
signal declination with distance from the transmitter, although the
signal does not drop off as one might expect (1/distance.sup.2 in
free space). This illustrates the importance of a correlation
between the resulting geopolygons generated with a predictive model
and the sensed signals using receiver hardware. In other words, the
"signal level" recorded by the test hardware, representative of
production receiver hardware, does not necessarily have a direct
correspondence to the Electromagnetic Field Levels that will be
generated by a predictive model. This reaffirms the utility of a
simple comparison methods, such as the declining threshold, whereby
the location of the receiver is determined using only the most
prevalent data trends (e.g., signal peaks). The general trend
observed in FIGS. 10 and 11 also show how that signals degrade
gradually with distance as opposed to sudden loss of reception.
This phenomenon significantly aids in the determination of location
and direction, as the method of comparison can use weaker signal
peaks to resolve the receiver location within a parent region
defined by stronger signal peaks. If signal reception terminated
suddenly, such granularity would not be obtainable.
[0123] Another observation that can be made from the results of the
Waterloo-Toronto drive test is related to sources of noise. Between
20 km and 100 km from the transmitter, the noise displays two main
trends. Higher order noise, most likely corresponding to local
clutter (both fixed and moving), transmitter variations, varying
antennae gain characteristics, and local weather conditions can be
observed at all distances. Lower frequency noise can also be
observed, and is more obvious at distances further from the
transmitters. As the transmitters selected are located in Toronto,
distances further away correspond to areas with less ground clutter
(hence less high frequency noise), thus making the low frequency
effects more visible. This suggests that the lower frequency noise
corresponds to more prevalent sources of error such as terrain
effects. A full spectral analysis of the data shown in FIGS. 9 and
10 could be used to provide appropriate error bounds that can be
applied to the signal at any distance from the transmitter.
[0124] More isolated tests have been conducted to verify the
relationship between the various frequencies of noise and their
sources. A stationary test was conducted in the Waterloo area, in a
relatively flat area with very little visible terrain variation and
almost no ground clutter in the immediate area. The purpose of the
test was to determine the error associated with variations in the
radiated power from the transmitters, with variable antennae gain
characteristics, and with weather conditions between transmitter
and receiver. It should be noted that it is difficult to
distinguish between these sources of noise with real-time data
tests. From an operational perspective, there is no need to
distinguish between them, as long as the error bounds are
considered reasonable. Thus, these sources of error can be
considered as one. It should also be noted that, even in such a
remote location, local traffic was not completely absent. FIG. 12
illustrates the measurements that were made. The few spikes present
in FIG. 12 correspond to times when vehicles passed by. This leads
to an important observation, the effects of transmitter, antennae,
and weather variations are much smaller than those due to local
clutter. FIGS. 13 (before normalization) and 14 (after
normalization) show the stationary FM signature for this test
location. It is clear from these plots that the average signal
error is much less than that shown in FIGS. 7 and 8 (corresponding
to moving tests), reaffirming the observation that signal
variations due to transmitter, antennae, and weather effects are
much less than those associated with ground clutter and terrain. As
a point of interest, it is also noted that the signature for the
stationary location (further outside of town than for the moving
test) is slightly different from that obtained from the moving
Waterloo drive test (FIGS. 7 and 8).
[0125] Some receiver-dependent characteristics also affect the
sensed FM signature. In particular, the signal floor resulting from
hardware limitations (DC offset, settling time) or from ambient
noise in the FM band can significantly affect the form of the FM
signature. As shown in FIG. 7, the un-normalized signature for the
Waterloo region suggests signal reception from a wide variety of FM
channels for which there are no transmitters present. Using the
declining threshold method, only the peaks of the signature are
important defining characteristics (and in FIG. 7, the peaks of
96.7, 98.5, 100.3, and 105.3 seem to be the most prevalent). A
normalized version of the FM signature with the floor offset
removed is shown in figure FIG. 8. This local normalization
emphasizes the defining peaks as relative values to all other
frequencies. Again, it is clear that FM frequencies 96.7, 98.5,
100.3, and 105.3 are the most important defining frequencies, but
the normalized plot also makes several other useful results more
apparent. In particular, 88.3, 89.9, 91.5, 92.1, and 95.3 are
displayed as peaks above the nominal values in the lower FM band.
Based on transmitter registration data, the frequency 92.1 is
broadcast from Brantford, Ontario; the frequency 88.3 is broadcast
from Paris, Ontario; and the frequency 95.3 is broadcast from
Hamilton, Ontario. Since Brantford, Paris, and Hamilton are all
within broadcast range of the Waterloo region, it makes sense that
their signals would appear as peaks in the Waterloo FM signature.
Since 89.9 and 91.5 are both broadcast from Windsor and Ottawa,
both of which are too far from Waterloo for there to be a signal
included in Waterloo's FM signature, and since a manual radio
tuning to these frequencies resulted in audio radio reception, it
is evident that the database of transmitters relied upon must not
be complete. Building a database of signature-based regions from an
incomplete list of transmitters would result in an incomplete or
inaccurate database.
[0126] It should also be noted that the normalized data also
emphasizes the error associated with the various signals while
driving around the Waterloo region. This error, along with those
obtained through other targeted drive tests can be used as a
calibration source. In this particular case, the major peaks
corresponding to transmitters in the Waterloo/Kitchener region are
sufficient to place the receiver within Waterloo, and the inclusion
of the low-power University of Waterloo radio station (100.3)
subdivides this region into two areas. The inclusion of additional
signals from surrounding regions will most likely serve to
subdivide the region further (distinguishing the southern reception
areas for Waterloo/Kitchener transmitters from their northern
regions). Another important observation relevant to signal
calibration is the presence of spectral leakage for frequencies
close to those of certain transmitters. Since transmitters in a
larger (parent) region are usually separated by more than 200 kHz,
the occurrence of an FM signature with two adjacent FM peaks is
usually representative of spectral leakage (easily observed by
tuning the radio to the next possible FM channel and being able to
make out the sounds of the adjacent FM channel). The term "spectral
leakage" is used loosely here because it is not clear whether or
not this effect is due to transmitter properties or due to receiver
properties. That is, it is possible that hardware limitations on
the FM tuner cause this apparent problem. In some embodiments, this
phenomenon is taken into consideration in the method of comparison,
so that signatures with and without adjacent signals are considered
for matching with known signatures.
[0127] In preferred embodiments, the various sources of noise are
accounted in order to improve the accuracy of the comparisons that
are made. As described above, several tests (both stationary and
moving) were performed to identify and isolate the various sources
of noise. These tests resulted in the following observations.
[0128] Sources of noise include receiver limitations and variations
(DC offset, settling time, saturation); atmospheric (cloud cover,
precipitation, pressure); multipath due to fixed objects (terrain,
stationary obstacles); multipath due to moving objects (other
vehicles); and transmitter limitations and variations (power
fluctuations). Wherever possible, noise should be taken into
consideration in the development of the radio signatures 39 so that
computation is minimized in the receiver. Only fixed sources of
noise can be accounted for in this manner (terrain and stationary
objects).
[0129] Receiver limitations will vary from receiver to receiver,
and so must be taken into account locally (if any attempt is made
to account for such effects). Preferably, a method of sensing that
removes (or minimizes) this error should be used before signal
processing is done so that one method of comparison can be used for
all receivers.
[0130] For sample data that isn't saturated (due to receiver
limitations), the noise displays two main trends. Higher order
noise, most likely corresponding to local clutter (both fixed and
moving), transmitter variations, varying antennae gain
characteristics, and local weather conditions. Lower frequency
noise can also be observed, and is more obvious at distances
further from the transmitters. As the transmitters used for the
testing described above are located in Toronto, distances further
away correspond to areas with less ground clutter (hence less high
frequency noise), thus making the low frequency effects more
visible. This suggests that the lower frequency noise corresponds
to more prevalent sources of error such as terrain effects.
[0131] It is extremely difficult to distinguish between noise due
to transmitter variations, antennae limitations, and weather
variations in a live environment. Additionally, stationary tests
revealed that the effects of transmitter, antennae, and weather
variations are much smaller than those due to local clutter.
Several methods for dealing with the various sources of noise are
presented below.
5.11 Sampling Rate
[0132] Through the use of the test hardware described above (used
to represent the limitations of existing tuner modules), it was
determined that the effects of settling time, as a result of
frequency switching, can be minimized simply by using the average
values of a large set of sample data. Thus each recorded value is
the average of many sampled values. Both the sampling rate and the
sampling interval can be selected to minimize this source of
noise.
5.12 Normalization
[0133] It is desirable to remove (or reduce) the noise associated
with receiver limitations before signal processing (or comparison)
is done, so that the same algorithm can be used for all receivers.
Through the various drive tests, it was observed that, close to a
transmitter (typically within 20 km for high power transmitters),
the recorded signal appeared to be saturated. It was also noted
that there appeared to be a signal floor (minimum value higher than
0), most likely corresponding to a DC offset in the tuner module.
While these receiver limitations have no real ill effect on the FM
signature at a particular location, very little information about
the noise characteristics of the signal can be gleaned in these
ranges. Normalizing the data (removing the DC offset, and only
considering non-saturated values) with receiver specific
configuration values provides a receiver-independent data set that
can then be analyzed. This data set was then amplified (as part of
the normalization process) to increase the separation between data
peaks. This was done to improve the quality of the signal
processing. It should be noted that, while this amplification also
served to exaggerate the effect of noise in the signature, it most
likely increased the stability of the comparison method by reducing
its required sensitivity.
5.13 Windowing
Peak Isolation
[0134] Another important observation relevant to signal calibration
is the presence of spectral leakage for frequencies close to those
of certain transmitters. Since transmitters in a larger (parent)
region are usually separated by more than 200 kHz, the occurrence
of an FM signature with two adjacent FM peaks suggests spectral
leakage (easily observed by tuning the radio to the next possible
FM channel and being able to make out the sounds of the adjacent FM
channel). The term "spectral leakage" is used loosely here because
it is not clear whether or not this effect is due to transmitter
properties or due to receiver properties. That is, it is possible
that hardware limitations on the FM tuner cause this apparent
problem. In preferred embodiments, this phenomenon is taken into
consideration in the method of comparison, so that signatures with
and without adjacent signals are considered for matching with known
signatures.
[0135] Only signal peaks are used in signature comparison in
preferred embodiments of the present invention. For example, in the
experiments described above, a simple windowing method was used to
remove the apparent "spectral leakage", and to isolate the true
signal peaks. As this processing must be done in real time,
in-vehicle, the simplest possible windowing method was used. For a
particular window size, only consider the maximum value within the
window. The size of the window is chosen to reflect the typical
separation between active FM transmitter frequencies (so that the
true signal peaks are not removed from the signature).
5.14 Peak Detection
[0136] A declining threshold method (FIG. 3) can be used with
either an empirical model or a predictive model, as not all sources
of error can be accounted for in either model. The declining
threshold method also has the advantage of simplicity, requiring
minimal computation by effectively ignoring all but the most
pertinent data. This method also provides for various levels of
granularity, with very course predictions given almost instantly,
and a more refined prediction after each iteration, until an exact
match is found.
[0137] Through drive tests, especially in the Waterloo area
(described above), various observations were made that illustrate
the benefits of the methods implemented in the present invention.
First, the tests indicate that peak data is sufficient for the
unique determination of the receiver's location within the target
area (Canada and the Continental United States). Second, the
general trend of recorded signal declination with distance from the
transmitter is not necessarily as one might expect
(1/distance.sup.2 in free space). That is to say, the signal level
recorded by the test hardware (representative of production
receiver hardware) does not necessarily have a direct
correspondence to the Electromagnetic Field Levels that will be
generated by a predictive model. Thus, with the use of a predictive
model that determines what the Electromagnetic Field strength
should be at particular locations, a simple method of comparison
could be used that is, more or less, independent of the particular
unit of measure used. The declining threshold method is useful in
this respect, as it can serve to compare to similar, but not
identical, entities.
[0138] Third, signals degrade gradually with distance (as opposed
to sudden loss of reception). This will significantly aid in the
determination of location and direction, as the method of
comparison will use weaker signal peaks to resolve the receiver
location within the parent region (determined using stronger signal
peaks). While a direct binary comparison (the signal is either
present or not present) might return the same signature for two
similar regions, the declining threshold method will provide the
order in which individual signals should be considered, thereby
differentiating between two similar regions with slightly different
signal strengths.
[0139] Fourth, the method of comparison cannot be done
algorithmically using transmitter registration information alone,
as there are currently no defined relationships between the
registrations for different cities. That is, until the transmitters
are displayed geographically and the broadcast regions are
geo-encoded (or until a sufficiently granular set of empirical
baseline data points are generated), there is no way to determine
that the transmitter information data for two cities can be
combined to form a single signature (as there is no way to
algorithmically determine whether or not two cities are close to
each other based on transmitter registration data).
5.15 Advanced Error Propagation Models
[0140] As discussed earlier, wherever possible, fixed sources of
noise should be taken into account when generating radio signatures
39 so that the amount of real-time computation (comparison) can be
minimized.
[0141] It is not entirely clear how well empirical models account
for the sources of noise. While the signatures at the exact
recorded locations reflect the actual signature that will be
received at that particular location, the signatures received
within the same region, but not at that particular location, may
not be identical. To illustrate, assume that reference data is
collected in a grid-like manner, at points separated by 10 km. Each
reference signature, then, would represent a 10 km by 10 km area.
All received signatures in that area will not be identical
(especially in an urban environment where there is significant,
varying ground clutter). Two ways to avoid this problem with an
empirical model include: reducing the grid size to improve
accuracy, or using averages values in a region to determine a
single representative FM signature. Reducing the grid size could
yield extremely accurate results, but with significant cost in
terms of development and maintenance. Using averaged values makes
the inclusion of noise in the model less clear. What sort of
processing would be required on a receiver to match such an
averaged reference signature is, as yet, unknown.
[0142] Ideally, a model that includes specific sources of noise
accurately, and other sources of noise not at all, would provide
for a robust system of comparison in which the receiver is
responsible for filtering out only particular sources of noise. An
empirical model with a very small grid size would be ideal for such
a system, but very impractical to implement.
[0143] A predictive model that takes into account the effects of
terrain and fixed clutter is suitable. This leaves the receiver
with the following sources of noise to filter out: receiver
limitations (which can be accounted for as described in the
previous sections), atmospheric and transmitter variations (which
have minimal effects, as discussed previously), and moving objects.
In addition to helping minimize the effects of receiver
limitations, using time-averaged values can also help to reduce the
error associated with moving objects. Thus, a predictive model that
can account for terrain and fixed clutter effects is a preferred in
some embodiments of the present invention.
6. CONCLUSION
[0144] All references cited herein are incorporated herein by
reference in their entirety and for all purposes to the same extent
as if each individual publication or patent or patent application
was specifically and individually indicated to be incorporated by
reference in its entirety for all purposes.
[0145] The present invention can be implemented as a computer
program product that comprises a computer program mechanism
embedded in a computer readable storage medium. For instance, the
computer program product could contain the program modules shown in
FIG. 1. These program modules may be stored on a CD-ROM, DVD,
magnetic disk storage product, or any other computer readable data
or program storage product. The software modules in the computer
program product can also be distributed electronically, via the
Internet or otherwise, by transmission of a computer data signal
(in which the software modules are embedded) on a carrier wave.
[0146] Many modifications and variations of this invention can be
made without departing from its spirit and scope, as will be
apparent to those skilled in the art. The specific embodiments
described herein are offered by way of example only, and the
invention is to be limited only by the terms of the appended
claims, along with the full scope of equivalents to which such
claims are entitled.
* * * * *
References