U.S. patent application number 10/182615 was filed with the patent office on 2003-06-19 for positioning.
Invention is credited to Lobo, Natividade, Overy, Michael.
Application Number | 20030114115 10/182615 |
Document ID | / |
Family ID | 26243550 |
Filed Date | 2003-06-19 |
United States Patent
Application |
20030114115 |
Kind Code |
A1 |
Overy, Michael ; et
al. |
June 19, 2003 |
Positioning
Abstract
A receiver for calculating its position according to a first
transmitter, having a processor arranged to convolve: the
probability density function representing the position of the first
transmitter, sent by the first transmitter to the receiver; with
the probability density function representing the likelihood that a
transmission from the first transmitter will be successfully
received at the receiver.
Inventors: |
Overy, Michael; (Hants,
GB) ; Lobo, Natividade; (Berks, GB) |
Correspondence
Address: |
ANTONELLI TERRY STOUT AND KRAUS
SUITE 1800
1300 NORTH SEVENTEENTH STREET
ARLINGTON
VA
22209
|
Family ID: |
26243550 |
Appl. No.: |
10/182615 |
Filed: |
October 22, 2002 |
PCT Filed: |
February 2, 2001 |
PCT NO: |
PCT/GB01/00440 |
Current U.S.
Class: |
455/73 ;
342/463 |
Current CPC
Class: |
G01S 7/40 20130101; G01S
13/876 20130101; H04W 64/00 20130101; G01C 21/14 20130101; G01S
5/02 20130101; G01S 5/0289 20130101; G01C 21/00 20130101 |
Class at
Publication: |
455/73 ; 342/463;
455/41 |
International
Class: |
G01S 003/02; H04B
001/38 |
Foreign Application Data
Date |
Code |
Application Number |
Feb 2, 2000 |
GB |
0002404.2 |
Aug 7, 2000 |
GB |
0019366.4 |
Claims
1. A receiver for calculating its position according to a first
transmitter, having a processor arranged to convolve: (i) the
probability density function representing the position of the first
transmitter, sent by the first transmitter to the receiver; with
(ii) the probability density function representing the likelihood
that a transmission from the first transmitter will be successfully
received at the receiver.
2. A receiver as claimed in claim 1 for calculating its position
according to a second transmitter, having a processor arranged to
convolve: (i) the probability density function representing the
position of the second transmitter, sent by the second transmitter
to the receiver; with (ii) the probability density function
representing the likelihood that a transmission from the second
transmitter will be successfully received at the receiver.
3. A receiver as claimed in any preceding claim wherein the
probability density function representing the likelihood that a
transmission from the first transmitter will be successfully
received at the receiver is an approximation which simplifies
processing.
4. A receiver as claimed in claim 2 or 3, wherein the probability
density function representing the likelihood that a transmission
from the first transmitter will be successfully received at the
receiver is the same as the probability density function
representing the likelihood that a transmission from the second
transmitter will be successfully received at the receiver.
5. A receiver as claimed in claim 1 for calculating its position
according to a plurality of transmitters, having a processor
arranged to calculate a probability density function for each of
said plurality of transmitters by the convolution of (i) the
probability density function representing the position of one of
the plurality of said transmitters, sent by said one transmitter to
the receiver; with (ii) the probability density function
representing the likelihood that a transmission from said one
transmitter will be successfully received at the receiver and
arranged to combine the resultant plurality of probability density
functions.
6. A receiver as claimed in claim 5 wherein the combination of the
resultant probability density functions involves pair-wise
combination of probability density functions.
7. A receiver as claimed in claim 6 wherein the pair-wise
combination involves the multiplication of one probability density
function with another.
8. A receiver as claimed in claim 5 wherein the pair-wise
combination involves the addition of one probability density
function with another.
9. A receiver as claimed in claim 7 or 8, wherein the combination
is a weighted combination.
10. A receiver as claimed in claim 9 wherein the weighted
combination increases the contribution made from probability
density functions derived from trusted transmitters.
11. A receiver as claimed in any preceding claim wherein the
transmitters are not permanent infrastructure.
12. A method of calculating the position of a receiver by
communication with a plurality of transceivers comprising the steps
of, for each of said plurality of transmitters, convolving (i) the
probability density function representing the position of a
transmitter, sent by the transmitter to the receiver; with (ii) the
probability density function representing the likelihood that a
transmission from the transmitter will be successfully received at
the receiver and combining the plurality of convolution
products.
13. A method as claimed in claim 12 wherein the receiver is the
Master transceiver in an ad-hoc network of Bluetooth transceivers
and the plurality of transmitters are Slave transceivers in that
Bluetooth network.
Description
[0001] The present invention relates to the positioning of a
transceiver using other transceivers. It has particular application
to the positioning of a transceiver by forming an ad hoc network of
transceivers without the use of a dedicated infrastructure.
[0002] It is often desirable to be able to determine one's position
or to determine the position of another person or device. The
Global position system (GPS) allows the location of specialist
receivers to be positioned on the surface of the earth. GPS uses a
fixed network of satellite transmitters orbiting the earth to
transmit to and thereby locate the receiver. Cellular positioning
systems have also been proposed in which the existing network of
fixed base station transceivers is used to locate a mobile phone.
The unchanging position and identity of the fixed base stations and
the distance of the mobile phone from the base stations is used to
estimate the phones location. Both of these systems operate over
large distances exceeding many kilometres.
[0003] It would be desirable to provide a system by which the
location of persons or objects can be determined wirelessly but
without having to invest in a dedicated fixed network of radio
receivers.
[0004] It would be desirable to re-use existing wireless
technology, which may be provided for a different purpose, to allow
position determination.
[0005] For a better understanding of the present invention and to
understand how the same may be brought into effect reference will
now be made by way of example only to the accompanying drawings in
which:
[0006] FIG. 1 illustrates a distribution of transceivers T;
[0007] FIG. 2 illustrates an exemplary probability density function
representing the chances of successful transmission between
transmitter and receiver as the distance between transmitter and
receiver varies;
[0008] FIG. 3 illustrates an exemplary probability density function
representing the probable location of a transceiver on the x-axis;
and
[0009] FIG. 4 illustrates a transceiver.
[0010] FIG. 1 illustrates a transceiver Ti which is capable of
forming an ad hoc network 2 via radio communications with the
transceivers Tj. The network may be formed by Ti acting as a Master
with the transceivers Tj functioning as Slaves. Preferably the
transceivers are Bluetooth transceivers and the network is a
piconet. When the transceiver Ti acquires its position it forms a
network with neighbouring transceivers Tj which have already
acquired their positions. The communication range of transceiver Ti
is illustrated by the circle 4. There are a number of transceivers
Tj which are outside the range 4 and cannot participate in the
network 2.
[0011] The transceiver Ti, once it has acquired its position it can
participate as a Slave in a different network formed by another
transceiver to acquire its position. Each of the transceivers T are
the same. Each acts as a Master to form a network with Slave
transceivers to acquire a position and then it can participate as a
Slave in a different network formed by another transceiver to
acquire its position. The transceivers T are not infrastructure.
They are preferably integrated into host devices such as mobile
phones, desk telephones, computers etc. The transceivers which are
available to participate in a network may therefore vary as
transceivers move into and out of range of the Master
transceiver.
[0012] Referring to FIG. 1, the transceiver Ti is attempting to
determine its position. It forms a network with N transceivers Tj
where j=1, 2, 3 . . . N.
[0013] The probability that a transceiver Tj can transmit
successfully to the transceiver Ti when separated by distance y is
given by prob.sub.TransSuccessful.ji[y]. The probability density
function representing the probability a transceiver j can transmit
successfully to the Transceiver Ti is given by
pdf.sub.TransSuccessful.ji[y]
[0014] where 1 pdf TransSuccessful .. ji [ y ] = prob
TransSuccessful ji [ y ] - .infin. .infin. prob TransSuccessful ji
[ y ] y
[0015] If all transmitters Tj are equal,
prob.sub.TransSuccessful.ji[y] may be replaced by
prob.sub.TransSuccessful[y] which represents the probability that
any one of the transceivers Tj can transmit successfully to the
transceiver Ti when separated by distance y. The probability
density function representing the probability a transceiver j can
transmit successfully to any one of the Transceiver Ti is given by
Pdf.sub.TransSuccessful.ji[y] where 2 pdf TransSuccessful [ y ] =
prob TransSuccessful [ y ] - .infin. .infin. prob TransSuccessful [
y ] y
[0016] FIG. 2 illustrates an exemplary probability density function
representing the chances of successful transmission between a
transmitter and receiver Ti as the distance between transmitter and
receiver varies. The probability density function may be based on
measurements for example by sounding the communication channel
between transmitter and receiver. The probability density function
may be an approximation, chosen to ease subsequent calculations.
The illustrated probability density function is an approximation
which eases subsequent calculations. It assumes that within a
certain range of the transmitter the chances of reception are good
and constant, but at a certain threshold distance from the
transmitter the chances of reception decrease proportionally with
the distance travelled from the threshold.
[0017] The transceivers T are preferably positioned in three
dimensions with respect to three orthogonal linear axes. Although
this is not essential, it provides advantages because the
positioning of a transceiver with respect to one of the axes is
independent of the positioning with respect to the other two axes.
The transceiver is therefore positioned in three dimensions by
positioning it separately with respect to each axes. In the
following description the positioning of a transceiver Ti with
respect to one axes is described. Analogous procedures are carried
out for the remaining axes.
[0018] Each transceiver is positioned with respect to the linear
axis using a probability density function. The transceiver Tj is
positioned with respect to the linear axis by pdf.sub.j[z] where
the argument indicates a position of the transceiver Tj from an
origin common to the transceivers Tj . The function pdf.sub.j[z]
varies as the argument varies having a maximal value at where the
most likely acquired position for transceiver Tj is. The
transceiver Ti will acquire its position by calculating a
probability density function pdf.sub.i[z] for itself.
[0019] FIG. 3 illustrates an exemplary probability density function
pdf.sub.i[z] representing the probable location of a transceiver on
the x-axis, where z represents a distance along the x-axis.
[0020] When the transceiver Ti is acquiring its position, it
receives pdf.sub.j[z] from each of the N transceiver Tj where j=1,
2, 3 . . . N. That is it receives pdf.sub.1[z] from T1,
pdf.sub.2[z] from T2, pdf.sub.3[z] from T3, etc.
[0021] If all transmitters Tj are equal, there is no necessity for
each of the transmitters j to send prob.sub.TransSuccessful.ji[y].
The values of prob.sub.TransSuccessful[y] may be stored in Ti.
However, if the transmitters Tj have different transmission
characteristics such as different transmission power levels then it
may be appropriate for each of the transceivers Tj to transmit
prob.sub.TransSuccessful.ji[y] to the transceiver Ti.
[0022] On the basis of this information the transceiver Ti can
calculate its position according to a first order calculation. This
first order calculation takes into account, the transceivers Tj
with which the transceiver Ti can directly communicate. The
calculation determines where the transceiver Ti could be because it
can communicate with the transceivers Tj.
[0023] The transceiver Ti can calculate its position density
function pdf.sub.i[z], which takes into account all the
transceivers Tj, by combining the intermediate probability density
functions pdf.sub.ij[y] calculated because the particular
Transceiver Tj can communicate with Ti, for all j.
[0024] The intermediate probability density functions pdf.sub.ij[y]
calculated because the particular Transceiver Tj can communicate
with Ti is given by: 3 pdf ij [ y ] = ( - .infin. .infin. pdf j [ ]
prob TransSuccessful ji [ y - ] ) - .infin. .infin. ( - .infin.
.infin. pdf j [ ] prob TransSuccessful ji [ y - ] ) y
[0025] This can be converted using mathematics to: 4 pdf ij [ y ] =
- .infin. .infin. pdf j [ ] pdf TransSuccessful ji [ y - ]
[0026] The probability density function representing the position
of the receiver Ti is therefore given by the convolution of the
probability density function representing the position of the
transmitter Tj with the probability density function representing
the likelihood of successful transmission from the transmitter to
receiver.
[0027] The transceiver Ti can calculate its position density
function pdf.sub.i[z], which takes into account all the
transceivers Tj, by combining the intermediate probability density
functions pdf.sub.ij[y] calculated because the particular
Transceiver Tj can communicate with Ti as follows: 5 pdf i [ y ] =
j = 1 N j pdf ij [ y ] y ' ( j = 1 N j pdf ij [ y ' ] ) where j = 1
N j = 1
[0028] where .alpha..sub.j is a parameter which represents how
trustworthy the Transceiver Tj is. For example, if the transceiver
Tj is a reference station it will have a high value, whereas if the
transceiver Tj is very mobile it will have a low value. It should
be appreciated that the values .alpha..sub.j may be transmitted by
transceiver Tj to transceiver Ti (although renormalisation will be
required such that .SIGMA..alpha..sub.j=1) , or the values of
.alpha..sub.j may be calculated by Ti on the basis of information
received from the transceivers Tj such as other indications of
their trustworthiness.
[0029] The use of trustworthiness in the calculation can be
disabled by setting .alpha..sub.j=1 for all j.
[0030] The above calculation of pdf.sub.i[z] effectively determines
the renormalised overlap of the probability density functions
pdf.sub.ij[z] (taking into account their trustworthiness if
appropriate) for all j. A problem, however, arises if the
probability density functions pdf.sub.ij[z] do not overlap.
[0031] A preferred method of combining the intermediate probability
density functions pdf.sub.ij[y] takes into account that the
intermediate probability density functions pdf.sub.ij[y] may not
all overlap. The method combines the intermediate probability
density functions in a pair-wise fashion. If the pair of
probability density functions which are to be combined do overlap
the method calculates the renormalised overlap of the two
intermediate probability density functions. However, if the pair of
probability density functions which are to be combined do not
overlap, the method calculates a weighted sum of the two
probability density functions.
[0032] One manner of implementing the preferred method will now be
described. In this preferred method the transceiver Ti, before it
has acquired its new position, may have no current position or may
have a position which has expired. If the current position has
expired the variable pdf.sub.i(old)[y] is set equal to the current
expired value of pdf.sub.i[y]. If there is no current position the
variable pdf.sub.i(old)[y] is set equal to 0. A temporary variable
pdf.sub.iTemp.j[y] is assigned for use in the calculation. It is
initially set for j=0, equal to pdf.sub.i(old)[y]. The temporary
variable pdf.sub.iTemp.j-1[y], is combined in a pair-wise fashion
with pdf.sub.i.j[y], starting with the pair-wise combination of
variable pdf.sub.iTemp.0[y] with pdf.sub.i.1[y] to produce
pdf.sub.iTemp.1[y], then the pair-wise combination of
pdf.sub.iTemp.1[y] with pdf.sub.i.2[y] to produce
pdf.sub.iTemp.2[y], etc., ending with the pair-wise combination of
pdf.sub.iTemp.N-1[y] with pdf.sub.i.N[y] to produce
pdf.sub.iTemp.2[y] which is the position of Ti (pdf.sub.i[y]))
taking into account only the first order transceivers Tj, for j=1,
2, 3 . . . N.
[0033] The method can be coded as follows:
[0034] Start Code:
[0035] Initial condition: pdf.sub.iTemp.0[y]=pdf.sub.i(old)[y]
[0036] Body of the loop started with j=1 and exited at j=N
[0037] {
[0038] (Test for overlap between pdf.sub.iTemp.j-1[y] &
pdf.sub.ij[y]) 6 If y ' pdf iTempj - 1 [ y ' ] pdf ij [ y ' ] 0
then
[0039] (If there is overlap, calculate the renormalised overlap) 7
pdf iTempj = pdf iTempj - 1 y j pdf ij y y ' ( pdf iTempj - 1 [ y '
] pdf ij [ y ' ] )
[0040] else
[0041] (If there is no overlap, calculate a weighted sum)
[0042]
pdf.sub.iTempj[y]=pdf.sub.iTempj-1[y]+.alpha..sub.jpdf.sub.ij[y]
[0043] }End of loop
[0044] Final result: pdf.sub.i[y]=pdf.sub.iTemp.N[y]
[0045] End Code
[0046] Thus far the value of pdf.sub.i[y] representing the position
of the transceiver Ti, takes into account only the transceivers
Tj{j=1,2, . . . N}, which can communicate directly with the
transceiver Ti. Each of the transceivers Tj may be able to directly
communicate directly with transceivers with which the transceiver
Ti is unable to directly communicate. Such transceivers are second
order transceivers as the transceiver Ti which is acquiring its
position cannot communicate to them directly but can receive
information about them from the transceivers it can communicate
with. Information about the second order transceivers can be used
to additionally refine pdf.sub.i[y] so that it takes account not
only of where the transceiver Ti could be because it can directly
communicate with transceivers Tj but also where it could not be
because it cannot communicate with the second order
transceivers.
[0047] Let each of the second order transceivers be designated by
Tk, where k.noteq.j and k.noteq.i, k=1,2 . . . M.
[0048] In the above coding, the loop is directly followed and the
"Final result" is directly preceded by the coding:
[0049] Body of the loop started with k=1 and exited at k=M 8 { prob
noreception ki [ y ] = pdf k [ ] ( 1 - prob TransSuccessful ki [ y
- ] ) pdf iTempk = pdf iTempN y prob noreception ki y y ' ( pdf
iTempN [ y ] prob noreception ki [ y ] ) pdf iTemp N [ y ] = pdf
iTemp k [ y ] } end of loop
[0050] It will be necessary for the transceiver to receive the
values of pdf.sub.k[y] via the first order transceivers which are
in communication with the second order transceivers.
[0051] Likewise prob.sub.TransSuccessful.ki[y] should also be
transmitted to Ti via the first order transceivers Tj. However, if
all the second order transceivers are the same then
prob.sub.TransSuccessful.ki[y] will be a constant and can be
stored. According to a one embodiment, the approximate value
prob.sub.TransSuccessful[y] which was used in the first order
calculations is also used in the second order calculations.
[0052] The probability density function representing a position of
a transceiver will normally have a normal distribution as
illustrated in FIG. 3. Advantages can be achieved by assuming such
pdfs have a normal distribution. The completed information required
to define a normal distribution is the mean and the standard
deviation. Consequently the probability density function
representing the position of a transceiver can be transmitted using
only two parameters--the mean and standard deviation.
[0053] FIG. 4 illustrates a transceiver suitable for carrying out
the invention. It comprises transmitter circuitry, receiver
circuitry, a processor and a memory. The memory stores the above
described algorithm. The processor executes the algorithm. The
parameters used as input to the algorithm are stored in the memory
and the result of the algorithm, the position of the transceiver,
is also stored in the memory. When the transceiver operates as a
receiver, to acquire its position, it receives the parameters it
requires for the algorithm from the transceivers it is in
communication with and stores them in the memory. When the
transceiver operates as a transmitter, it is operable to transmit
its stored position to the receiving transceiver using its
transmission circuitry. The algorithm may be transported for
transfer to a transceiver using a carrier such as a CD-ROM or
floppy disc.
[0054] Although the present invention has been described in the
preceding paragraphs with reference to various examples, it should
be appreciated that modifications and variations to the examples
given can be made without departing from the spirit and scope of
the invention.
* * * * *