U.S. patent application number 16/128004 was filed with the patent office on 2019-08-22 for system and method for location boosting using proximity information.
This patent application is currently assigned to CommScope Technologies LLC. The applicant listed for this patent is CommScope Technologies LLC. Invention is credited to Khalid W. Al-Mufti, Martin C. Alles, Andrew E. Beck, Thomas B. Gravely.
Application Number | 20190261300 16/128004 |
Document ID | / |
Family ID | 45688288 |
Filed Date | 2019-08-22 |
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United States Patent
Application |
20190261300 |
Kind Code |
A1 |
Alles; Martin C. ; et
al. |
August 22, 2019 |
SYSTEM AND METHOD FOR LOCATION BOOSTING USING PROXIMITY
INFORMATION
Abstract
A system and method for determining the location of a target
mobile device in a communications network. A set of mobile devices
in proximity to the target mobile device may be determined (210) as
a function of a common parameter of information observed by mobile
devices in the set. Measurement data may be shared (220) for the
set of mobile devices and the target mobile device, and a location
of the target mobile device (230) determined as a function of the
shared measurement data. This sharing of measurement data may occur
amongst the set of mobile devices and the target mobile device or
may also occur at a communication network entity.
Inventors: |
Alles; Martin C.; (Vienna,
VA) ; Gravely; Thomas B.; (Herndon, VA) ;
Al-Mufti; Khalid W.; (Sterling, VA) ; Beck; Andrew
E.; (Ashburn, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
CommScope Technologies LLC |
Hickory |
NC |
US |
|
|
Assignee: |
CommScope Technologies LLC
Hickory
NC
|
Family ID: |
45688288 |
Appl. No.: |
16/128004 |
Filed: |
September 11, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15603514 |
May 24, 2017 |
10085230 |
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16128004 |
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13984463 |
Nov 24, 2014 |
9693333 |
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PCT/US12/24483 |
Feb 9, 2012 |
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15603514 |
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61441118 |
Feb 9, 2011 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 4/023 20130101;
G01S 5/0036 20130101; G01S 5/0072 20130101; H04W 64/003 20130101;
H04W 88/02 20130101; H04W 24/10 20130101 |
International
Class: |
H04W 64/00 20060101
H04W064/00; H04W 4/02 20060101 H04W004/02; G01S 5/00 20060101
G01S005/00 |
Claims
1. A method of determining the location of a target mobile device
in a communications network, the method comprising: selecting a set
of mobile devices to be used in locating the target mobile device,
wherein the mobile devices are selected according to a function
based on a common parameter of information observed by the mobile
devices, and wherein each mobile device in the set of mobile
devices is configured to originate and/or terminate communications
with the communications network; determining a location of one or
more mobile devices in the set; sharing the determined location
amongst mobile devices in the set and the target mobile device; and
determining a location of the target mobile device as a function of
the shared determined locations.
2. The method of claim 1, wherein determining a location of the
target mobile device comprises selecting from the group consisting
of a location of one mobile device in the set, a centroid of
locations of mobile devices in the set, a straight average of
locations of mobile devices in the set, a weighted average of
locations of mobile devices in the set, and a weighted average and
a straight average of mobile devices in the set.
3. The method of claim 1, wherein determining a location of the
target mobile device further comprises: determining a location for
the set of mobile devices, and determining the location of the
target mobile device as a function of determined location for the
set.
4. The method of claim 3, wherein determining the location of the
set of mobile devices comprises determining the location of the set
of mobile devices is selected from the group consisting of
determining a location of one mobile device in the set, determining
a centroid of locations of mobile devices in the set, determining a
straight average of ones of the locations of mobile devices in the
set, determining a weighted average of ones of the locations of
mobile devices in the set, determining a weighted average and a
straight average of ones of the mobile devices in the set, and
combinations thereof.
5. A program product for determining the location of a target
mobile device in a communications network, tangibly stored on a
non-transitory storage medium in a mobile device, comprising
instructions operable to cause at least one programmable processor
to do the following: selecting a set of mobile devices to be used
in locating the target mobile device, wherein the mobile devices
are selected according to a function based on a common parameter of
information observed by the mobile devices, and wherein each mobile
device in the set of mobile devices is configured to originate
and/or terminate communications with the communications network;
determining a location of one or more mobile devices in the set;
sharing the determined location amongst mobile devices in the set
and the target mobile device; and determining a location of the
target mobile device as a function of the shared determined
locations.
6. The method of claim 5, wherein determining a location of the
target mobile device comprises selecting from the group consisting
of a location of one mobile device in the set, a centroid of
locations of mobile devices in the set, a straight average of
locations of mobile devices in the set, a weighted average of
locations of mobile devices in the set, and a weighted average and
a straight average of mobile devices in the set.
7. The method of claim 5, wherein determining a location of the
target mobile device further comprises: determining a location for
the set of mobile devices, and determining the location of the
target mobile device as a function of determined location for the
set.
8. The method of claim 7, wherein determining the location of the
set of mobile devices comprises determining the location of the set
of mobile devices is selected from the group consisting of
determining a location of one mobile device in the set, determining
a centroid of locations of mobile devices in the set, determining a
straight average of ones of the locations of mobile devices in the
set, determining a weighted average of ones of the locations of
mobile devices in the set, determining a weighted average and a
straight average of ones of the mobile devices in the set, and
combinations thereof.
9. A method for determining the location of a target mobile device,
the method comprising: identifying the target mobile device;
identifying an unplanned set of other mobile devices in proximity
with the target mobile device, wherein each mobile device in the
unplanned set of mobile devices is configured to originate and/or
terminate communications with a communications network; and
determining the location of the target mobile device based on a set
of data provided by the unplanned set of mobile devices in
proximity to the target mobile device and by the target mobile
device.
Description
CROSS REFERENCES
[0001] The present application is a continuation of U.S. patent
application Ser. No. 15/603,514, which is a continuation of U.S.
patent application Ser. No. 13/984,463, which is a national stage
application of PCT application number PCT/US2012/024483, which
claims the benefit of provisional application Ser. No. 61/441,118,
filed on Feb. 9, 2011, the entirety of which is incorporated herein
by reference.
BACKGROUND
[0002] Applicant's disclosure is generally directed towards the
location of a mobile device within a communications network. There
are many traditional methods of locating a mobile device including,
but not limited to, handset-based techniques and network-based
techniques. These techniques may include, but are not limited to,
Assisted-Global Positioning Satellite (A-GPS), Uplink Time
Difference of Arrival (U-TDOA), Observed TDOA (O-TDOA), Enhanced
Observed Time Difference (E-OTD), Electronic Cell Identification
(E-CID), Radio Frequency (RF) fingerprinting, and Multiple Range
Estimation Location (MREL) techniques, to name a few. Such
techniques, however, may be ineffective in locating mobile devices
in certain challenging environments, e.g., urban environments,
indoor environments, etc.
[0003] Several telecommunications industry reports have indicated a
higher usage of mobile devices in such challenging environments as
well as higher usage of location based applications in recent
years. Mobile devices operating in these environments may be
blocked from receiving GPS signals due to the signal attenuation of
the satellite signals by building infrastructure and/or other
environmental aspects. This same infrastructure may also attenuate
the signals transmitted by cellular towers such that cellular
service may be unavailable. Such challenging environments often
provide a paucity of positional or location measurements that would
enable determining the location of mobile devices. This
insufficiency of measurements may lead to a poor location estimate
for the mobile device and/or an inability of the respective system
or device to generate the location estimate. One example of such
insufficient measurements may occur during the location of a mobile
device inside a building, under heavy cloud cover, or when
obstructed by large structures. These situations may arise in the
context of A-GPS location and/or terrestrial location
determinations, with or without Location Measurement Units (LMU),
or in any combination thereof. Additionally, even in RF pattern
matching schemes, an indoor mobile device may provide poor RF
signatures as exemplary schemes may rely upon calibration data
obtained in the outdoor environment.
[0004] Therefore, there is a need in the art for a system and
method to improve location capabilities of a communications system
in such environments. There is a further need in the art to
increase or boost the number of available positional measurements
for the location determination of a mobile device.
[0005] In view of these needs, one embodiment of the present
subject matter provides a method of determining the location of a
target mobile device in a communications network. The method may
include determining a set of mobile devices in proximity to the
target mobile device as a function of a common parameter of
information observed by mobile devices in the set and sharing
measurement data amongst the set of mobile devices and the target
mobile device. A location of the target mobile device may then be
determined as a function of the shared measurement data.
[0006] Another embodiment of the present subject matter provides a
method of determining the location of a target mobile device in a
communications network. The method may include determining a set of
mobile devices in proximity to the target mobile device as a
function of a common parameter of information observed by mobile
devices in the set. Measurement data from mobile devices in the set
and from the target mobile device may be transmitted to a
communications network entity. A location of the target mobile
device may then be determined as a function of both the transmitted
measurement data from the set of mobile devices and the transmitted
measurement data from the target mobile device.
[0007] A further embodiment of the present subject matter may
provide a method of determining the location of a target mobile
device in a communications network. The method may include
determining a set of mobile devices in proximity to the target
mobile device as a function of a common parameter of information
observed by mobile devices in the set and determining locations of
one or more mobile devices in the set. The determined locations may
be shared amongst mobile devices in the set and the target mobile
device. A location of the target mobile device may then be
determined as a function of the shared determined locations.
[0008] An additional embodiment of the present subject matter may
provide a method of determining the location of a target mobile
device in a communications network. The method may include
determining one or more common parameters of information for mobile
devices in proximity to the target mobile device and identifying a
set of mobile devices as a function of the determined one or more
common parameters. A location of the target mobile device may be
determined as a function of the measurement data from the set of
mobile devices.
[0009] Another exemplary embodiment for determining the location of
a target mobile device in a communications network may include
determining a set of mobile devices in proximity to the target
mobile device as a function of a common parameter of information
observed by mobile devices in the set and then determining a
location of the target mobile device as a function of measurement
data from the determined set of mobile devices.
[0010] These and other embodiments of the present subject matter
will be readily apparent to one skilled in the art to which the
disclosure pertains from a perusal or the claims, the appended
drawings, and the following detailed description.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 is a diagram of a basic architecture for an
embodiment of the present subject matter.
[0012] FIG. 2 is a block diagram of one embodiment of the present
subject matter.
[0013] FIG. 3 is a block diagram of a further embodiment of the
present subject matter.
[0014] FIG. 4 is a block diagram of an additional embodiment of the
present subject matter.
[0015] FIG. 5 is a block diagram of another embodiment of the
present subject matter.
DETAILED DESCRIPTION
[0016] With reference to the figures, where like elements have been
given like numerical designations to facilitate an understanding of
the present subject matter, the various embodiments of a system and
method for location boosting using proximity information are
described.
[0017] Embodiments of the present subject may generally determine
the location of a mobile device by proximity detection by
recognizing the need for a mobile device to be located. This may be
accomplished by, for example, a tasking message provided by
cellular network equipment monitoring calls (e.g., 911 detection),
by scanning receivers located in the proximity of a region of
location coverage, by a user of the mobile device itself requesting
a location. One or more proximity sensors in the network may also
be tasked to receive signals from the mobile transmission of
interest and/or measure transmission signal quality. Measurements
may then be compiled from the tasked proximity sensors or other
network components and the location of the mobile device
determined. Exemplary methods for proximity detection are described
in co-pending U.S. patent application Ser. No. 12/986,439, entitled
"System and Method for Mobile Location by Proximity Detection,"
filed on Jan. 7, 2011, the entirety of which is incorporated herein
by reference.
[0018] FIG. 1 is a diagram of a basic architecture for an
embodiment of the present subject matter. With reference to FIG. 1,
a mobile device 103 of interest may be in communication with a base
station 106 in an exemplary communications network 100. A
Geolocation Control System (GCS) 101 in the network 100 may receive
tasking from a Tasking Server (TS) 104. The TS 104 may be operably
connected to other components 105 of the communications network
100. In one embodiment, the network 100 may also include one or
more Proximity Sensors (PS) 102 and/or Location Measurement Units
(LMU). These PSs 102 may receive a location request from the GCS
101 and may attempt to detect the mobile device 103 of interest.
Any one or each PS 102 may also report the quality of its detection
measurements to the GCS 101. The GCS 101 may then utilize these
reports to determine a location of the mobile device 103.
[0019] In other embodiments of the present subject matter, the TS
104 may be embedded in certain network core components (e.g.,
Serving Mobile Location Center (SMLC), etc.). The TS 104 may also
be embedded within one or more PSs 102 (to receive off-the-air
tasking). Alternatively, the TS 104 may be supplied by an
independent receiver apparatus, the PS 102 may be embedded in a
complementary repeater or Distributed Antenna System (DAS), and
LMUs (not shown) may be situated at the base station 106.
[0020] Embodiments of the present subject matter may increase or
boost the number of available positional measurements by
considering a set, subset or even the entirety of measurements
available to mobile devices in proximity to the mobile device whose
location is desired (i.e., target mobile device). It should be
noted that the terms position, positional and/or location are used
interchangeably in this disclosure and such use should not limit
the scope of the claims appended herewith. Generally, positional
measurements such as, but not limited to, Time Difference of
Arrival (TDOA) measurements, GPS pseudoranges, MREL measurements,
and the like, may possess errors due to environmental conditions,
etc. Thus, in embodiments of the present subject matter where
positional measurements pertinent to mobile devices in proximity to
the target mobile device are combined with the positional
measurements for the target mobile device, a larger measurement set
may be available to determine a location of the target mobile
device. This larger measurement set representative of the
measurements of a group of mobile devices may be an accidental,
unplanned organization of multiple mobile devices into the group
such that members of the group or set are proximate to each other.
It should be noted that the terms set and group are used
interchangeably in this disclosure and such use should not limit
the scope of the claims appended herewith. Further, this group may
also be visualized as a single, physically distributed sensor with
a membership that is not necessarily permanent.
[0021] Such an exemplary group may be formed by determining any one
or more common features of observed positional measurements at the
sensors of the mobile devices. For example, observation
measurements may be made by mobile devices on a Bluetooth radio
channel, another radio or television signal, and/or a Wi-Fi signal,
etc. Depending upon the particular observed measurement, the
interpretation given to the word proximity may change. Thus, if the
group or a subset of the group all see the same, for example, Wi-Fi
access point or Verizon Personal HotSpot, then this may provide an
estimate or interpretation for the proximity of the group's
members. That is, this common observable may define a distance
regarding the maximum distance apart members of the group are to
each other. Exemplary common observables or parameters may be, but
are not limited to, a Wi-Fi access point, Bluetooth radio channel
information, Wi-Fi signal information, radio frequency (RF) signal
parameter of signal transmissions from the mobile device, channel
number information, channel frequency information, timeslot
information, network timing information, range information,
spreading code information, received signal strength indications,
signal to noise ratios (SNR), ratios of energy per bit over power
spectral density of noise and interference (Eb/Io), ratios of
received pilot energy over power spectral density of noise and
interference (Ec/Io), dialed number information, an identification
of the mobile device, an international mobile subscriber identity
(IMSI), a temporary mobile subscriber identity (TMSI), a mobile
identification number (MIN), an electronic serial number (ESN), an
international mobile equipment identity (IMEI), a class mark
indicator, overhead transmission indicator, media access control
(MAC) address, IP address, available time assistance information,
satellite-in-view information, network timing information, range
measurement information to a terrestrial site, and combinations
thereof. By way of further example, if the observed measurements
were made by the group on or via a Bluetooth Piconet, then the
group's proximity may be on the order of 100 m. Of course,
additional exemplary parameters may include attribute(s) of
measurements or sets of measurements made by mobile devices. For
example, if a first mobile device has range measurements with
respect to sites [A, B and C] and a second mobile device TDOA
measurements with respect to sites [A, B] and [A, C], then an
exemplary parameter may be the fact that both the first and second
mobile devices have measurements against the common set of sites
[A, B, C]. Thus, the general principle to be emphasized is that the
group or subset thereof may share some features in which each
feature or group of features has some defining proximity or common
parameter.
[0022] Exemplary groups according to an embodiment of the present
subject matter may be identified in various methods. For example,
mobile devices may mutually share information with each other. As a
function of this sharing of information, the devices may
cooperatively define the group. In another embodiment, an external
observer or entity, e.g., the wireless communications network or
component thereof, may determine that some number of mobile devices
in the network defines or constitutes a group. In this embodiment,
the members of the group may be unaware that they are indeed a
member of the group and may not even directly communicate with each
other; thus, the network may define the group and combine and/or
share positional measurements from mobile devices in the group
and/or measurements from the target mobile device.
[0023] Once the group has been identified and/or defined,
positional measurements may be shared between or amongst members of
the group. As mentioned above, this sharing of positional
measurements may occur peer-to-peer between members of the group or
any number of members of the group may report measurements to the
network whereby the network combines and/or shares the
measurements. Thus, by considering these measurements collectively,
the group of mobile devices and individual members thereof may now
be located with a higher precision than any of its members prior to
such consideration. That is, the location accuracy of every member
of the group may now be improved with knowledge of the positional
measurements for other members of the group. For example, by
combining positional measurements of a target mobile device with
positional measurements of one or more other mobile devices in
proximity to the target mobile device, errors associated with
positional measurements from any of the devices in the group may be
limited by the degree of proximity among the group's members and by
the errors in the respective measurements. Thus, even when faced
with not being able to perform a location determination for the
target mobile device alone, having even one measurement from a
distant member in a proximate group may allow the target mobile
device to determine at least an estimated location where previously
there was none.
[0024] In additional embodiments of the present subject matter,
once the shared measurement process has occurred, a location
calculation for the group may be performed by one of the members of
the group, may be performed in some distributed fashion over the
members of the group, or may be performed at a network entity. In
these embodiments, the group itself may have an associated
location.
[0025] In one non-limiting example, a user of a mobile device has
an application available on his or her device that activates when
9-1-1 is dialed or when the network sends a high priority message
to the mobile device. When this application is activated, the
mobile device may, for example, establish a connection to a
Bluetooth network and may establish connections to other Bluetooth
enabled devices in its vicinity. This group may be formed utilizing
the Bluetooth protocol, and mobile devices may also be linked
together to form groups using a Bluetooth Scatternet (an extension
of a Bluetooth Piconet). One embodiment may identify a group of
mobile devices in terms of their respective TMSI or other mobile
device common parameter as noted above. Upon determining such a
common feature or parameter, Bluetooth MAC addresses or another
parameter may also be employed to serve as linked identifiers to
the TMSI, that is, the network may maintain a database associating
the Bluetooth MAC address with the TMSI to provide the network with
necessary information to call for any additional positional
measurements. The application on the mobile device may then, in one
embodiment, share the MAC addresses between the participating
mobile devices in the group. A first group of mobile devices
proximate to the target mobile device may then be determined from
the Bluetooth MAC addresses. The target mobile device or one of the
mobile devices in the first group may provide the identifying or
defining group information back to the network whereby the network
initiates a location request to the members of the first group.
This request may result in multiple positional measurement sets for
all mobile devices proximate to the target mobile device. Such
measurement data may now be available to boost or increase the
location information for the target mobile device and other devices
in the group. Of course, any other variations of this exemplary
process are possible. For example, in an emergency and if there are
insufficient measurements with the first group of mobile devices,
the network can activate similar applications on all or any of the
mobile devices in the group sharing the same serving sector, timing
advance band, etc. Thus, in certain embodiments, participation of
mobile devices in a group may be compelled on an emergency
basis.
[0026] Furthermore, mobile devices in a group may be chained or
linked. For example, a first group of mobile devices may lead to a
second group or subgroup of the first group and so forth to an nth
group whereby the nth group may generally represent the expected
reach of the respective air interface protocol signals from the
target mobile device. Thus, if the positional measurements of the
nth group were needed to be combined or shared with those of the
target mobile device, one may be provided with an estimation of how
accurately a location of the target mobile device can be achieved.
This chained or linked process may be applied to a scenario where
the target mobile device is located on a high floor of a building
and the chained location process works its way down to the street
level where there is a mobile device with positional measurements
that may be fruitfully combined with the positional measurements
(or lack thereof) from the target mobile device to determine a
location for the target mobile device. Thus, if this street level
mobile device can be independently located, then the number of
hops, N, may provide an estimation of what floor the target mobile
device is on or at least may set an upper bound for the location of
the target mobile device. In this instance, an exemplary property
of certain protocols, such as but not limited to Bluetooth, would
be the limited range of the protocol which may enhance the accuracy
of the location of a respective group or target mobile device. In
protocols having a larger range, combined location estimates may
possess a larger variance in their errors, thus other features or
parameters may be employed to define the group. Accordingly,
exemplary features defining a group may be such that members of the
group have a desired proximity to each other whereby the specific
proximity varies according to the respective communications
protocol.
[0027] In a network-based definition for the previous example,
mobile devices may report observed Bluetooth MAC addresses in their
proximity back to the network. The network may then determine what
constitutes a group based upon which mobile devices are in view of
other mobile devices. The network may then request members of the
group to report their positional measurements and may determine a
location for the group and/or may refine this location individually
for each member or certain subgroups. Exemplary positional
measurements and measurement data may include, but are not limited
to, Angle-of-Arrival (AOA) data, Observed
Time-Difference-of-Arrival (OTDOA) data, Enhanced-OTD (E-OTD) data,
Enhanced Cell-ID (E-CID) data, global navigation satellite system
(GNSS) data, assisted global navigation satellite system (A-GNSS)
data, uplink time of arrival (TOA) data, downlink TOA data, uplink
TDOA (U-TDOA) data, Wi-Fi data, Multiple Range Estimation Location
(MREL) data, Radio Frequency (RF) fingerprinting data, and
combinations thereof. For example, in the case of RF Fingerprinting
data, if a first mobile device observes signals from sites A and B
having respective power levels PA, PB, and a second mobile device
in the same proximity group observes signals from sites C and D
having respective power levels Pc, PD, then an exemplary RF
fingerprinting method applied to embodiments of the present subject
matter may match power levels for the site set [ABC D] given by [PA
PB Pc Pn] against a calibration database. The resultant solution
may then provide a location to the group containing the first and
second mobile devices. Thus, embodiments of the present subject
matter may incorporate the aggregation of RF fingerprinting type
measurements, as it would any other type of measurement.
[0028] In another embodiment, one mobile device in a group may
already possess a determined location which it may share directly
with other devices in the group or to the network in which the
members of the group may assign as their own location.
Alternatively, a mobile device may have enough positional
measurements to perform a location determination which it performs
and then shares with the group or network. In one embodiment, the
network, having knowledge what constitutes the membership of the
group, may assign the location of any one or several of the members
of the group as the location of a previously determined member. In
such instances, embodiments of the present subject matter are
sharing determined locations rather than just sharing positional
measurements. For example, if one member of the group has no
location information while all or some of the other members have
location information, the network may assign an average of the
known locations to the desired location of this member. Of course,
such an example should not limit the scope of the claims appended
herewith as any number of metrics of locations may be applied
including, but not limited to, a location of one mobile device in
the group, a centroid of locations of mobile devices in the group,
a straight average of ones of the locations of mobile devices in
the group, a weighted average of ones of the locations of mobile
devices in the group, a weighted average and a straight average of
ones of the mobile devices in the group, and combinations thereof.
Thus, it is an aspect of embodiments of the present subject matter
to resolve location problems that are currently intractable due to
varying degrees of accuracy.
[0029] To provide a non-limiting example of measurement sharing,
members of a group may share their GPS pseudo-range measurements,
depending upon the type of time assistance available to the mobile
devices in the group, when the location of the group is requested
by the network, the sharing operation may differ. For example, if
the network is capable of only providing coarse-time assistance
information to the GPS-capable mobile devices, then the location
server may combine the pseudo-ranges from different mobile devices.
Thus, if a first mobile device in the group has Satellites A and B
in view and a second mobile device in the group has Satellites C
and D in view, then pseudo-ranges A through D may be combined to
locate the group. In another embodiment, if fine-time assistance is
available for individual mobile devices within the group, then even
if a single pseudo-range from each device is available, i.e., each
mobile device has a different satellite in view, the positional
measurements may be combined to determine an approximate location
of the group, assuming the group in this example includes four or
more mobile devices. In another embodiment, if fine-time assistance
is unavailable, a post correction technique may be applied at the
location server. Such an exemplary technique may require mobile
devices in the group to report a network timing to GPS measurement
relationship (e.g., the GSM frame number relative to which it
determined the GPS frame offset, or pseudo ranges) to the location
server. Further, a location server that can obtain the network
timing to GPS time relationship (e.g., via LMUs that located within
the network) may alternatively remove GPS time uncertainty from the
positional measurements thereby allowing the location server to
combine the pseudo-range measurements in pairs, single
measurements, or otherwise.
[0030] In another example, a group may include four mobile devices
each of which has a range measurement to a terrestrial site. In
this example, the first mobile device of the group is capable of
locating itself irrespective of whether the device had access to
the measurements of other members in the group. Further, the first
mobile device in this example has a larger range measurement to the
terrestrial site than any of the other mobile devices in the group.
A location server may examine these measurements and conclude that
the first mobile device had an erroneous or multipath measurement
and may replace this erroneous measurement with an average of the
other three measurements. In this example, the first mobile device,
while capable of locating itself, is provided with a mechanism for
significantly increasing its location accuracy by using the
information collectively available in the group. Thus, the spatial
diversity of each member of the group has increased as a result of
being identified in this group.
[0031] FIG. 2 is a block diagram of one embodiment of the present
subject matter. With reference to FIG. 2, a method 200 of
determining the location of a target mobile device in a
communications network is provided. In step 210, a set of mobile
devices in proximity to the target mobile device may be determined
as a function of a common parameter of information observed by
mobile devices in the set. In one embodiment, step 210 may include
determining the set of mobile devices cooperatively by devices in
the set as a function of the shared measurement data or the
determination may be performed by a communications network entity.
Further, in step 210 a subset of mobile devices may be identified
as a function of a second parameter whereby the second parameter is
not common to each mobile device in the set of mobile devices.
Exemplary common parameters may be, but are not limited to, a Wi-Fi
access point, Bluetooth radio channel information, Wi-Fi signal
information, radio frequency (RF) signal parameter of signal
transmissions from the mobile device, channel number information,
channel frequency information, timeslot information, network timing
information, range information, spreading code information,
received signal strength indications, SNRs, Eb/Io, Ec/Io, dialed
number information, an identification of the mobile device, IMSI,
TMSI, MIN, ESN, IMEI, a class mark indicator, overhead transmission
indicator, MAC address, IP address, available time assistance
information, satellite-in-view information, network timing
information, range measurement information to a terrestrial site,
and combinations thereof. Exemplary measurement data may be, but is
not limited to, AOA data, OTDOA data, E-OTD data, E-CID data, GNSS
data, A-GNSS data, uplink TOA data, downlink TOA data, U-TDOA data,
Wi-Fi data, MREL data, RF fingerprinting data, and combinations
thereof.
[0032] In step 220, measurement data may be shared amongst the set
of mobile devices and the target mobile device. At step 230, a
location of the target mobile device may be determined as a
function of the shared measurement data. In one embodiment, step
230 may include determining a location for the set of mobile
devices and determining the location of the target mobile device as
a function of the determined location for the set. In yet another
embodiment, step 230 may include correcting measurement data from
either the target mobile device or a mobile device in the set using
the shared measurement data and determining the location of the
target mobile device as a function of the corrected measurement
data. Exemplary locations for the set of mobile devices may be, but
are not limited to, a location of one mobile device in the set, a
centroid of locations of mobile devices in the set, a straight
average of locations of mobile devices in the set, a weighted
average of locations of mobile devices in the set, and a weighted
average and a straight average of mobile devices in the set. In a
further embodiment, step 230 may include transmitting a location
request to mobile devices in the set, providing measurement data
from mobile devices in the set to a network entity in response to
the location request, and determining a location of the target
mobile device as a function of a set of the provided measurement
data.
[0033] Another exemplary embodiment for determining the location of
a target mobile device in a communications network may include
determining a set of mobile devices in proximity to the target
mobile device as a function of a common parameter of information
observed by mobile devices in the set and then determining a
location of the target mobile device as a function of measurement
data from the determined set of mobile devices. In a further
embodiment, the step of determining a location of the target mobile
device further may include sharing measurement data amongst the set
of mobile devices and the target mobile device and determining the
location using the shared data.
[0034] FIG. 3 is a block diagram of a further embodiment of the
present subject matter. With reference to FIG. 3, a method 300 of
determining the location of a target mobile device in a
communications network is provided. At step 310, a set of mobile
devices in proximity to the target mobile device may be determined
as a function of a common parameter of information observed by
mobile devices in the set. In one embodiment, step 310 may be
performed by the communications network entity. Measurement data
from mobile devices in the set and from the target mobile device
may be transmitted to a communications network entity at step 320.
At step 330, a location of the target mobile device may then be
determined as a function of both the transmitted measurement data
from the set of mobile devices and the transmitted measurement data
from the target mobile device. As noted above, exemplary common
parameters may include a Wi-Fi access point, Bluetooth radio
channel information, Wi-Fi signal information, RF signal parameters
of signal transmissions from the mobile device, channel number
information, channel frequency information, timeslot information,
network timing information, range information, spreading code
information, received signal strength indications, signal to noise
ratios, Eb/Io, Ec/Io, dialed number information, an identification
of the mobile device, IMSI, TMSI, MIN, ESN, IMEI, a class mark
indicator, overhead transmission indicator, MAC address, IP
address, available time assistance information, satellite-in-view
information, network timing information, range measurement
information to a terrestrial site, and combinations thereof.
Further, exemplary measurement data may be, but is not limited to,
AOA data, OTDOA data, E-OTD data, E-CID data, GNSS data, A-GNSS
data, uplink TOA data, downlink TOA data, U-TDOA data, Wi-Fi data,
MREL data, RF fingerprinting data, and combinations thereof.
[0035] FIG. 4 is a block diagram of an additional embodiment of the
present subject matter. With reference to FIG. 4, a method 400 for
determining the location of a target mobile device in a
communications network is provided. At step 410 a set of mobile
devices in proximity to the target mobile device may be determined
as a function of a common parameter of information observed by
mobile devices in the set. Locations of one or more mobile devices
in the set may be determined at step 420, and the determined
locations shared amongst mobile devices in the set and the target
mobile device at step 430. A location of the target mobile device
may then be determined at step 440 as a function of the shared
determined locations. The determined location of the target mobile
device may be a location of one mobile device in the set, a
centroid of locations of mobile devices in the set, a straight
average of locations of mobile devices in the set, a weighted
average of locations of mobile devices in the set, and a weighted
average and a straight average of mobile devices in the set. In one
embodiment, step 440 may include determining a location for the set
of mobile devices, and determining the location of the target
mobile device as a function of the determined location for the set.
Of course, in this alternative embodiment, the determined location
of the target mobile device may also be a location of one mobile
device in the set, a centroid of locations of mobile devices in the
set, a straight average of locations of mobile devices in the set,
a weighted average of locations of mobile devices in the set, and a
weighted average and a straight average of mobile devices in the
set.
[0036] FIG. 5 is a block diagram of another embodiment of the
present subject matter. With reference to FIG. 5, a method 500 is
provided for determining the location of a target mobile device in
a communications network. In step 510, one or more common
parameters of information for mobile devices in proximity to the
target mobile device may be determined, and in step 520 a set of
mobile devices identified as a function of the determined one or
more common parameters. In one embodiment, step 520 may include
determining the set of mobile devices cooperatively by devices in
the set as a function of the shared measurement data. Of course,
step 520 may be alternatively performed by a communications network
entity. A location of the target mobile device determined as a
function of measurement data from the set of mobile devices in step
530.
[0037] In one embodiment, step 530 may include sharing measurement
data from the set of mobile devices and from the target mobile
device whereby the location of the target mobile device is
determined as a function of the shared data. Further, this shared
data may occur amongst the set of mobile devices and the target
mobile device and/or may occur at a communications network
entity.
[0038] The present disclosure may be implemented by a general
purpose computer programmed in accordance with the principals
discussed herein. It may be emphasized that the above-described
embodiments, particularly any "preferred" embodiments, are merely
possible examples of implementations, merely set forth for a clear
understanding of the principles of the disclosure. Many variations
and modifications may be made to the above-described embodiments of
the disclosure without departing substantially from the spirit and
principles of the disclosure. All such modifications and variations
are intended to be included herein within the scope of this
disclosure and the present disclosure and protected by the
following claims.
[0039] Embodiments of the subject matter and the functional
operations described in this specification can be implemented in
digital electronic circuitry, or in computer software, firmware, or
hardware, including the structures disclosed in this specification
and their structural equivalents, or in combinations of one or more
of them. Embodiments of the subject matter described in this
specification can be implemented as one or more computer program
products, i.e., one or more modules of computer program
instructions encoded on a tangible program carrier for execution
by, or to control the operation of, data processing apparatus. The
tangible program carrier can be a computer readable medium. The
computer readable medium can be a machine-readable storage device,
a machine-readable storage substrate, a memory device, or a
combination of one or more of them.
[0040] The term "processor" encompasses all apparatus, devices, and
machines for processing data, including by way of example a
programmable processor, a computer, or multiple processors or
computers. The processor can include, in addition to hardware, code
that creates an execution environment for the computer program in
question, e.g., code that constitutes processor firmware, a
protocol stack, a database management system, an operating system,
or a combination of one or more of them.
[0041] A computer program (also known as a program, software,
software application, script, or code) can be written in any form
of programming language, including compiled or interpreted
languages, or declarative or procedural languages, and it can be
deployed in any form, including as a standalone program or as a
module, component, subroutine, or other unit suitable for use in a
computing environment. A computer program does not necessarily
correspond to a file in a file system. A program can be stored in a
portion of a file that holds other programs or data (e.g., one or
more scripts stored in a markup language document), in a single
file dedicated to the program in question, or in multiple
coordinated files (e.g., files that store one or more modules, sub
programs, or portions of code). A computer program can be deployed
to be executed on one computer or on multiple computers that are
located at one site or distributed across multiple sites and
interconnected by a communication network.
[0042] The processes and logic flows described in this
specification can be performed by one or more programmable
processors executing one or more computer programs to perform
functions by operating on input data and generating output. The
processes and logic flows can also be performed by, and apparatus
can also be implemented as, special purpose logic circuitry, e.g.,
an FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit).
[0043] Processors suitable for the execution of a computer program
include, by way of example, both general and special purpose
microprocessors, and any one or more processors of any kind of
digital computer. Generally, a processor will receive instructions
and data from a read only memory or a random access memory or both.
The essential elements of a computer are a processor for performing
instructions and one or more data memory devices for storing
instructions and data. Generally, a computer will also include, or
be operatively coupled to receive data from or transfer data to, or
both, one or more mass storage devices for storing data, e.g.,
magnetic, magneto optical disks, or optical disks. However, a
computer need not have such devices. Moreover, a computer can be
embedded in another device, e.g., a mobile telephone, a personal
digital assistant (PDA), a mobile audio or video player, a game
console, a Global Positioning System (GPS) receiver, to name just a
few.
[0044] Computer readable media suitable for storing computer
program instructions and data include all forms data memory
including non-volatile memory, media and memory devices, including
by way of example semiconductor memory devices, e.g., EPROM,
EEPROM, and flash memory devices; magnetic disks, e.g., internal
hard disks or removable disks; magneto optical disks; and CD ROM
and DVD-ROM disks. The processor and the memory can be supplemented
by, or incorporated in, special purpose logic circuitry.
[0045] To provide for interaction with a user, embodiments of the
subject matter described in this specification can be implemented
on a computer having a display device, e.g., a CRT (cathode ray
tube) or LCD (liquid crystal display) monitor, for displaying
information to the user and a keyboard and a pointing device, e.g.,
a mouse or a trackball, by which the user can provide input to the
computer. Other kinds of devices can be used to provide for
interaction with a user as well; for example, input from the user
can be received in any form, including acoustic, speech, or tactile
input.
[0046] Embodiments of the subject matter described in this
specification can be implemented in a computing system that
includes a back end component, e.g., as a data server, or that
includes a middleware component, e.g., an application server, or
that includes a front end component, e.g., a client computer having
a graphical user interface or a Web browser through which a user
can interact with an implementation of the subject matter described
is this specification, or any combination of one or more such back
end, middleware, or front end components. The components of the
system can be interconnected by any form or medium of digital data
communication, e.g., a communication network. Examples of
communication networks include a local area network (LAN) and a
wide area network (WAN), e.g., the Internet.
[0047] The computing system can include clients and servers. A
client and server are generally remote from each other and
typically interact through a communication network. The
relationship of client and server arises by virtue of computer
programs running on the respective computers and having a
client-server relationship to each other.
[0048] While this specification contains many specifics, these
should not be construed as limitations on the scope of the claimed
subject matter, but rather as descriptions of features that may be
specific to particular embodiments. Certain features that are
described in this specification in the context of separate
embodiments can also be implemented in combination in a single
embodiment. Conversely, various features that are described in the
context of a single embodiment can also be implemented in multiple
embodiments separately or in any suitable subcombination. Moreover,
although features may be described above as acting in certain
combinations and even initially claimed as such, one or more
features from a claimed combination can in some cases be excised
from the combination, and the claimed combination may be directed
to a subcombination or variation of a sub combination.
[0049] Similarly, while operations are depicted in the drawings in
a particular order, this should not be understood as requiring that
such operations be performed in the particular order shown or in
sequential order, or that all illustrated operations be performed,
to achieve desirable results. In certain circumstances,
multitasking and parallel processing may be advantageous. Moreover,
the separation of various system components in the embodiments
described above should not be understood as requiring such
separation in all embodiments, and it should be understood that the
described program components and systems can generally be
integrated together in a single software product or packaged into
multiple software products.
[0050] As shown by the various configurations and embodiments
illustrated in FIGS. 1-5, a method and system for location boosting
using proximity information have been described.
[0051] While preferred embodiments of the present subject matter
have been described, it is to be understood that the embodiments
described are illustrative only and that the scope of the invention
is to be defined solely by the appended claims when accorded a full
range of equivalence, many variations and modifications naturally
occurring to those of skill in the art from a perusal hereof.
* * * * *