GB2463714A - Determining the position of a mobile station in a wireless communication network - Google Patents
Determining the position of a mobile station in a wireless communication network Download PDFInfo
- Publication number
- GB2463714A GB2463714A GB0817489A GB0817489A GB2463714A GB 2463714 A GB2463714 A GB 2463714A GB 0817489 A GB0817489 A GB 0817489A GB 0817489 A GB0817489 A GB 0817489A GB 2463714 A GB2463714 A GB 2463714A
- Authority
- GB
- United Kingdom
- Prior art keywords
- mobile station
- determining system
- positioning server
- related data
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/0009—Transmission of position information to remote stations
- G01S5/0018—Transmission from mobile station to base station
- G01S5/0036—Transmission from mobile station to base station of measured values, i.e. measurement on mobile and position calculation on base station
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
Abstract
A position determining system is disclosed comprising a mobile station 10 and a positioning server 20. The mobile station 10 is connected to a wireless communication network 12 and provides position related data to the positioning server 20 via the wireless network 12. The positioning server 20 uses the position related data to determine the position of the mobile station 10 based on a priori knowledge of variable branch characteristics in a network of possible positions in which the mobile station 10 may be located. The variable branch characteristics are used with the position related data in a branch weighting algorithm evaluated by the positioning server 20 to determine the position of the mobile station 10 in a network of possible positions. The network of possible positions may comprise a road network. The variable branch characteristics may be time varying or position varying characteristics of the branch and may comprise one or more of expected speed, direction, acceleration, and expected radio signal measurements. The mobile station may comprise a mobile telephone.
Description
Position Determining The present invention relates to position determining, in particular but not exclusively to position determining methods, apparatus, systems and components thereof.
According to an aspect of the present invention there is provided a positioning determining system comprising a mobile station and a positioning server, wherein: the mobile station is arranged to generate position-related data and to provide said position-related data to the positioning server; the positioning server is arranged to receive said position-related data from the mobile station, and based on the received position-related data to determine the position of the mobile station in a network of possible positions by applying a branch weighting algorithm, the branch weighting algorithm employing knowledge of variable branch characteristics in determining the position of the mobile station in the network of possible positions.
According to an aspect of the present invention there is provided a positioning determining method employing a mobile station and a positioning server, wherein: the mobile station generates position-related data provides said position-related data to the positioning server; the positioning server receives said position-related data from the mobile station, and based on the received position-related data determines the position of the mobile station in a network of possible positions by applying a branch weighting algorithm, the branch weighting algorithm employing knowledge of variable branch characteristics in determining the position of the mobile station in the network of possible positions.
According to an aspect of the present invention there is provided a mobile station for use in the position determining system, and/or arranged to operate in the position determining method.
According to an aspect of the present invention there provided a positioning server for use in the position determining system, and/or arranged to operate in the position determining method.
Suitably, the network of possible positions comprises a network of nodes, with branches extending from and/or between the nodes. Suitably, the network or possible positions comprises a road network.
Suitably, the variable branch characteristics are one or more of time varying or position varying characteristics of the branch. Suitably, the variable branch characteristics comprise one or more of expected speed, expected direction, expected acceleration, and expected radio signal measurements. Suitably, the variable branch characteristics are determined a priori, for example being computed at least in part based on training data measured along the branches.
Suitably, the variable branch characteristics are determined a priori, for example being computed at least in part based on expect knowledge. Suitably, the branch characteristics are computed by the positioning server.
Suitably, the mobile station is arranged periodically or at irregular time intervals to generate position related-data, and the positioning server is arranged to employ position-related data from more than one point in time in determining the position of the mobile station.
Suitably, the mobile station is arranged to generate position-related data according to characteristics of locality in which the mobile station is positioned, the position-related data comprising one or more of: mobile station speed, mobile station acceleration, mobile station direction of travel, and radio signal measurements. Suitably, the mobile station comprises a compass. Suitably, the mobile station comprises an inertial navigation system. Suitably, the mobile station is arranged to receive radio signals from a mobile communication network.
Suitably, the mobile station comprises a mobile telephone.
Suitably, the mobile station is formed in a single unit with the positioning server.
For a better understanding of the invention, and to show how embodiments of the same may be carried into effect, reference will now be made, by way of example, to the accompanying diagrammatic drawings in which: Figure 1 shows an example position determining system; Figure 2a and 2b show a road map and a corresponding network of possible positions; Figure 3 shows an example of variable branch characteristics represented as branch membership functions; Figure 4 shows an example position determining method; and Figure 5 shows a Kalman filter architecture usable to post filter a most probable route, the most probable route determined with reference to an example embodiment of the invention.
Referring now to Figure 1 there is shown an example position determining system. The system comprises a mobile station 10 and a positioning server 20. The mobile station 10 is connected to a wireless communication network 12, and communicates with the positioning server 20 using the wireless communication network 12. The mobile station 10 provides position-related data to the positioning server 20 using the wireless communication network 12. In this embodiment the communication network 12 comprises a GSM network and the mobile station 10 comprises a GSM mobile phone.
The positioning server 20 uses the position-related data to determine the position of the mobile station 10 using a priori knowledge of variable branch characteristics in a network of possible positions in which the mobile station 10 may be located. The variable branch characteristics are used with the position-related data in a branch weighting algorithm evaluated by the positioning server 20 to determine the position of the mobile station 1 0 in a network of possible positions. The variable branch characteristics are stored in a branch characteristic database 22 accessible to the positioning server 20.
The variable branch characteristics are in this embodiment time varying characteristics of the branch. In this example embodiment the branches comprise roads in a road network. Figure 2a shows a road map, with road junctions identified with letters A-T. Figure 2b shows corresponding branches and nodes A-T in network of possible positions on the roads of Figure 2a.
The expected speed of movement of mobile stations on a branch will vary according to the time of day -average speed along certain roads in a road network is typically highest at night and slowest at periods of peak road usage. Such variable branch characteristics are determined a priori, being computed based on training data measured along the branches and fed back to the positioning server 20 by specialist positioning/training vehicles employed in establishing the branch characteristic database 22 in the positioning server 20.
The mobile station 10 periodically provides updates of the position-related data to the positioning server 20. In this embodiment the position-related data comprises speed information determined by an inertial navigation system in the mobile station 10, and radio signal information related to the strength of signals received from base stations 14 in the wireless communication network 12. The mobile station 10 may suitably provide a first level of filtering/processing of the raw physical signals and data that the mobile station 10 is able to receive/generate, with the position-related data provided to the positioning server comprising some or all of the raw and the filtered/processed signals and data. In another example embodiment the mobile station 10 comprises a compass.
The variable branch characteristics are used in the branch weighing algorithm to impart a weighting to a likely degree of membership associated with each branch. That is, the variable branch characteristics influence the likelihood of a position on each of the branches being the position to be determined, when the positioning server 20 analyses the position-related data received from the mobile station 10. More than one branch characteristic and/or more than one class of position-related data may contribute to an overall weighting for each branch, with the overall weighting calculated by aggregating component memberships according to the received position-related data and the predetermined membership functions.
Figure 3 shows an example of variable branch characteristics represented as branch membership functions relating speed to the time of day. At periods of peak road usage - 08:00-09.30 and 16:30-18:00 the characteristics for this branch are represented by the dashed line, which indicates a relatively higher likelihood of speeds below 15km/hour. The dotted line corresponds to the membership function applied during the period 09:30-1 6:30, and the solid line corresponds to the membership function applied overnight from 18:00 to 08:00.
Figure 4 shows an example position determining method. The first step Si 10 in the method is a preparatory step of gathering information on the network of possible positions. In the example embodiment described the network is a road network expressed in a standard vector format. The road vector information is converted into a static network of branches and nodes as shown in Figure 2b.
The second step S120 is generation of the variable branch characteristics. The variable branch characteristics are generated as described above, and for each branch the variable characteristics are stored, e.g. as a membership function in the branch characteristic database 22.
Artificial Intelligence (Al) techniques may usefully be employed in this step. The first approach to generating the variable branch characteristics is appropriate when a process of system learning is provided with a set of training data. The training data comprises a number of real dynamic position-related parameter measurements that are collected for the branches through real road tests. The training data is provided to an Al model in the positioning server which automatically estimates the membership functions for the branches. The models can be reinforced or updated when further training data becomes available.
The second approach is to design membership functions partially based on expert knowledge with the aid of Mamdani type fuzzy rules. For example, the membership function for a branch (bi) with dynamic input parameter speed (S) can be automatically generated by aggregating the following fuzzy rule-base: RULE-BASE Rs FOR PARAM "SPEED" IF speed limit =30 AND time=8:30 THEN membership function S= gauss2mf(x, [12 15 8 25]) IF speed limit =30 AND timel2:00 THEN membership function S= gauss2mf(x, [20 30 8 30]) IF speed limit =50 AJID time=8:30 THEN membership function S= gauss2mf(x, [12 30 8 30]) IF speed limit =50 AIID time=23:00 THEN membership function S= gauss2mf(x, [20 50 10 50]) This step can be completed either as a preparatory process for all the branches in the network, or as a real-time process in which the relevant (estimated) subsets of branches have branch characteristics generated when required.
The third step S130 is generation of the position-related data by the mobile station 10 and the provision of the position-related data to the positioning server 20. The position related data may itself be generated based on known branch characteristics, and as such the mobile station 10 provides a pre-filtering step to facilitate the overall position determining.
Furthermore, the position related data at a certain point in time may be generated with reference to earlier position related data and/or with earlier determined positions.
On receipt of the position-related data the positioning server determines the position of the mobile station 10 in the network of possible positions by applying a branch weighting algorithm. The branch weighting algorithm employs knowledge of the variable branch characteristics, e.g. by referring to the membership functions in the branch characteristic database.
This step is explained in more detail below: Measurements of position-related data are repeatedly taken in real-time (e.g. speed(1)=30.4 km/h, speed(2)=28.9 km/h,... speed(n)=20.1 km/h; time(1)=12:34:23, time(2)=1 2:34:24,... time(n)=1 2:39:48; etc.).
The component membership of each parameter of the position-related data is calculated for all relevant branches with the membership functions designed in step 120, e.g.: speed component membership (Ms) to branches bi b20: Ms,bl =Rs(s,t,bl); Ms,b2=Rs(s,t,b2) Ms,b20=Rs(s,t,b20); direction of travel component (d) membership (Md) to branch bi b20: Md,bl =Rd(d,t,bl); Md,b2=Rd(d,t,b2) Md,b20=Rd(d,t,b20); The memberships for each of the branches are collectively aggregated. The aggregation can be again based on simple criteria such as arithmetic mean, or calculation that involves expert knowledge, such as Centre of gravity (CoG) with a manually defined weight assign to each input. The CoG aggregation works as described below: Mbl = COG([Ms,bl Md,bl 1) Mb2 = COG([Ms,b2 Md,b2 1) Mb20 = COG([Ms,b20 Md,b20 1) Where Mbi is the overall membership for branch bi The position is then determined by the positioning server as a position on the overall most likely branch.
After the position has been determined, other supplementary steps may optionally be performed. The fourth step S140 is a step of most likely route estimation. In this step the probabilities evaluated in step S130 for each branch are used in a Viterbi or other suitable algorithm to determine a most probable route. Another supplementary step is a fifth step Si 50 of post filtering the most likely route information. This information is provided as an input to a motion model based filtering approach that may be used to calculate where the mobile terminal was at any point in time, and where the mobile terminal is envisaged to be given a specific time in the future. A bi-directional, multiple start-point, Kalman filtering algorithm is suitable, and operational efficient. Figure 5 illustrates the general operation of a conventional Kalman filter; however, due to the knowledge of past and/or future samples, within this example embodiment, the approach is for example simply extended within a Monte-Carlo analysis framework using different starting points and directions.
Possible modifications to the system include providing the database and server functionality in a single device, so that the combined mobile station/server are a single integrated unit capable of determining its own position. A position determined according to the systems and methods described herein my be provided, for example wirelessly, back to the mobile station. A position determined according the systems and methods described herein may be provided to a central location database 24 to be accessed for example by subscribers 26 as shown in Figure 1. In embodiments such as these the position information may be useful to emergency services etc. The position determining systems and methods described herein are able to operate in situations where satellite based positioning systems are ineffective. Also, by shifting computational work to a positioning server, relatively simple and power efficient mobile stations are possible. For example the relevant mobile station functionality is easily built into mobile phone handsets, in particular using a compass or other inertial navigation systems in a mobile phone handset, to be used to form the basis of a position report as mandated under US E91 1 requirements.
Attention is directed to all papers and documents which are filed concurrently with or previous to this specification in connection with this application and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference.
All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and/or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and/or steps are mutually exclusive.
Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.
The invention is not restricted to the details of the foregoing embodiment(s). The invention extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed.
Claims (9)
- Claims 1. A positioning determining system comprising a mobile station and a positioning server, wherein: the mobile station is arranged to generate position-related data and to provide said position-related data to the positioning server; the positioning server is arranged to receive said position-related data from the mobile station, and based on the received position-related data to determine the position of the mobile station in a network of possible positions by applying a branch weighting algorithm, the branch weighting algorithm employing knowledge of variable branch characteristics in determining the position of the mobile station in the network of possible positions.
- 2. The positioning determining system of claim 1, wherein the network of possible positions comprises a network of nodes, with branches extending from and/or between the nodes. 0)
- 3. The position determining system of claim 1 or 2, wherein the network of possible positions comprises a road network. o 20
- 4. The position determining system of any preceding claim, wherein the variable branch (\J characteristics are one or more of time varying or position varying characteristics of the branch.
- 5. The position determining system of any preceding claim, wherein the variable branch characteristics comprise one or more of expected speed, expected direction, expected acceleration, and expected radio signal measurements.
- 6. The position determining system of any preceding claim, wherein the variable branch characteristics are determined a priori, being computed at least in part based on training data measured along the branches.
- 7. The position determining system of any preceding claim, wherein the variable branch characteristics are determined a priori, being computed at least in part based on expect knowledge.
- 8. The position determining system of any preceding claim, wherein the positioning server is arranged to compute the variable branch characteristics.
- 9. The position determining system of any preceding claim, wherein the mobile station is arranged periodically or at irregular time intervals to generate position related-data, and the positioning server is arranged to employ position-related data from more than one point in time in determining the position of the mobile station.11. The position determining system of any preceding claim, wherein the mobile station comprises a compass.12. The position determining system of any preceding claim, wherein the mobile station comprises an inertial navigation system.13. The position determining system of any preceding claim, wherein the mobile station is arranged to receive radio signals from a mobile communication network.14. The position determining system of any preceding claim, wherein the mobile station comprises a mobile telephone. a)Q 15. The position determining system of any preceding claim, wherein the mobile station is arranged to generate position-related data according to characteristics of locality in which the Q 20 mobile station is positioned, the position-related data comprises one or more of: mobile station speed, mobile station acceleration, mobile station direction of travel, and radio signal measurements.16. The position determining system of any preceding claim, wherein the mobile station is formed in a single unit with the positioning server.17. A positioning determining method employing a mobile station and a positioning server, wherein: the mobile station generates position-related data provides said position-related data to the positioning server; the positioning server receives said position-related data from the mobile station, and based on the received position-related data determines the position of the mobile station in a network of possible positions by applying a branch weighting algorithm, the branch weighting algorithm employing knowledge of variable branch characteristics in determining the position of the mobile station in the network of possible positions.18. A mobile station for use in the position determining system of any one of claims 1-16, and/or arranged to operate in the position determining method of claim 17.19. A positioning server for use in the position determining system of any one of claims 1- 16, and/or arranged to operate in the position determining method of claim 17.20. A position determining system or method, or mobile station or positioning server for use therewith, substantially as herein described.21. A position determining system or method, or mobile station or positioning server for use therewith, substantially as herein described with reference to the accompanying drawings. a) (\J (\J
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB0817489A GB2463714A (en) | 2008-09-24 | 2008-09-24 | Determining the position of a mobile station in a wireless communication network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB0817489A GB2463714A (en) | 2008-09-24 | 2008-09-24 | Determining the position of a mobile station in a wireless communication network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB0817489D0 GB0817489D0 (en) | 2008-10-29 |
| GB2463714A true GB2463714A (en) | 2010-03-31 |
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ID=39952128
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| GB0817489A Withdrawn GB2463714A (en) | 2008-09-24 | 2008-09-24 | Determining the position of a mobile station in a wireless communication network |
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| Country | Link |
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| GB (1) | GB2463714A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1996039638A1 (en) * | 1995-06-05 | 1996-12-12 | Airnet Communications Corporation | Mobile telephone location process making use of handoff data |
| WO1996042179A1 (en) * | 1995-06-10 | 1996-12-27 | Phonelink Plc | Increasing the resolution in locating cellular telephones |
| US6108555A (en) * | 1996-05-17 | 2000-08-22 | Ksi, Inc. | Enchanced time difference localization system |
| EP1235076A1 (en) * | 2001-02-23 | 2002-08-28 | Cambridge Positioning Systems Limited | Improvements in positioning systems and methods |
| EP1302783A1 (en) * | 2001-10-10 | 2003-04-16 | Elisa Communications OYJ | Location of a mobile terminal |
| US20070050824A1 (en) * | 2001-02-02 | 2007-03-01 | Andy Lee | Location identification using broadcast wireless signal signatures |
-
2008
- 2008-09-24 GB GB0817489A patent/GB2463714A/en not_active Withdrawn
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1996039638A1 (en) * | 1995-06-05 | 1996-12-12 | Airnet Communications Corporation | Mobile telephone location process making use of handoff data |
| WO1996042179A1 (en) * | 1995-06-10 | 1996-12-27 | Phonelink Plc | Increasing the resolution in locating cellular telephones |
| US6108555A (en) * | 1996-05-17 | 2000-08-22 | Ksi, Inc. | Enchanced time difference localization system |
| US20070050824A1 (en) * | 2001-02-02 | 2007-03-01 | Andy Lee | Location identification using broadcast wireless signal signatures |
| EP1235076A1 (en) * | 2001-02-23 | 2002-08-28 | Cambridge Positioning Systems Limited | Improvements in positioning systems and methods |
| EP1302783A1 (en) * | 2001-10-10 | 2003-04-16 | Elisa Communications OYJ | Location of a mobile terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| GB0817489D0 (en) | 2008-10-29 |
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Legal Events
| Date | Code | Title | Description |
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| WAP | Application withdrawn, taken to be withdrawn or refused ** after publication under section 16(1) |