ESTIMATION OF POSITION USING WLAN ACCESS POINT RADIO PROPAGATION CHARACTERISTICS IN A WLAN POSITIONING SYSTEM

• US 20090154371A1
• Filed: 02/25/2009
• Published: 06/18/2009
• Est. Priority Date: 05/08/2006
• Status: Active Grant

• Current Assignee: Skyhook Wireless Incorporated (Liberty Broadband Corp.)
• Original Assignee: Skyhook Wireless Incorporated (Liberty Broadband Corp.)
• Inventors: Pahlavan, Kaveh, Alizadeh-Shabdiz, Farshid
• Granted Patent: US 7,916,661 B2
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: G01S 11/06 using intensity measurements
• CPC Class Codes: G01S 5/02521 using a radio-map
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

A method for estimating position using WLAN access point radio propagation characteristics in a WLAN location based service is provided. A location-based services system has a plurality of Wi-Fi access points in a target area. The Wi-Fi access points are positioned at geographic locations and have signal coverage areas. A method of characterizing at least one of the Wi-Fi access points comprises determining the geographic location of the Wi-Fi access point, dividing the signal coverage area of the Wi-Fi access point into at least one section, and determining radio propagation characteristics for each section. The radio propagation characteristics of each section characterize a radio channel of the Wi-Fi access point, and the characterization can be used in a location algorithm.

Claims

1. A method of characterizing at least one Wi-Fi access points, using the coverage area of the Wi-Fi access point, so that the characterization may be used later to effectively weigh signals transmitted by said Wi-Fi access point when performing a location estimation, the method of characterization comprising:

determining the geographic location of the Wi-Fi access points;

for each Wi-Fi access point, measuring a plurality of power values for signals transmitted by a corresponding Wi-Fi access point, each power value being measured at position relative to each corresponding Wi-Fi access point;

determining a signal coverage area of each Wi-Fi access point based on said measured plurality of power values;

dividing the signal coverage area of the Wi-Fi access point into at least two sections;

determining radio propagation characteristics for each section; and

assigning a weight to each section based on the coverage areas of the Wi-Fi access points,

where sections having relatively small coverage areas are assigned a higher effective weight than sections having relatively large coverage areas,

wherein the location estimation will bias its estimate of position to rely on signals detected from the Wi-Fi access points with relatively smaller coverage areas, even if said signals are detected with relatively weaker power than signals detected from Wi-Fi access points with larger coverage areas and relatively higher power.

2. The method of claim 1, wherein the sections are divided according to at least two radials from the Wi-Fi access point.

5. The method of claim 1, wherein the sections are divided according to at least one distance from the Wi-Fi access point.

6. The method of claim 5, wherein the number of distances is one.

7. The method of claim 1, wherein the sections are divided according to at least two radials and at least one distance from the Wi-Fi access point.

8. The method of claim 1, wherein the radio propagation characteristics include a signal power-distance gradient.

4. The method of claim 3, wherein the number of radials is six or less.

10. The method of claim 9, wherein the signal power-distance gradient for each section is determined by a method comprising:

performing a linear regression on the plurality of power values and associated positions; and

using a slope determined by the linear regression to calculate the signal power-distance gradient.

11. The method of claim 9, wherein the signal power-distance gradient for each section is determined by the method comprising:

calculating a distance corresponding to each of the power values, the distances being measured from the associated positions of the power values to the geographic locations of the Wi-Fi access points;

estimating a radius of signal coverage using the standard deviation of the distances; and

using the radius of signal coverage to calculate the signal power-distance gradient.

12. The method of claim 11, wherein the standard deviation of the distances, σ

, is calculated according to equations having the form

$\mathrm{\sigma <br><br>}=\sqrt{\frac{\underset{1}{\overset{N}{\sum <br><br>}}<br><br>{\left(d_i\right)}^2}{N-1}}<br><br>N><br><br>1$ $\mathrm{\sigma <br><br>}=0,N=1,$

wherein;

d_i is the distance of the associated position of received power value i from the location of the Wi-Fi access point; and

N is the number of power values.

13. The method of claim 11, wherein the signal power-distance gradient, α

, is calculated using equations having the form

$\mathrm{\alpha <br><br>}={\mathrm{\alpha <br><br>}}_{\min },\mathrm{if}<br><br><br><br>\left(\mathrm{\sigma <br><br>}><br><br>{\mathrm{\sigma <br><br>}}_{\max }\right)$ $\mathrm{\alpha <br><br>}={\mathrm{\alpha <br><br>}}_{\max },\mathrm{if}<br><br><br><br>\left(\mathrm{\sigma <br><br>}<<br><br>{\mathrm{\sigma <br><br>}}_{\min }\right)$ $\mathrm{\alpha <br><br>}={\mathrm{\alpha <br><br>}}_{\max }+\left({\mathrm{\alpha <br><br>}}_{\min }-{\mathrm{\alpha <br><br>}}_{\max }\right)<br><br>\left(\frac{\log <br><br>\left(\mathrm{\sigma <br><br>}\right)-\log <br><br>\left({\mathrm{\sigma <br><br>}}_{\min }\right)}{\log <br><br>\left({\mathrm{\sigma <br><br>}}_{\max }\right)-\log <br><br>\left({\mathrm{\sigma <br><br>}}_{\min }\right)}\right),<br><br>\mathrm{if}<br><br><br><br>\left({\mathrm{\sigma <br><br>}}_{\min }<<br><br>\mathrm{\sigma <br><br>}\le <br><br>{\mathrm{\sigma <br><br>}}_{\max }\right)$

wherein;

σ

_min is a minimum signal coverage threshold;

σ

_max is a maximum signal coverage threshold;

σ

is the average radius of signal coverage;

α

_min is a minimum signal power-distance gradient; and

α

_max is a maximum signal power-distance gradient.

14. The method of claim 13, wherein:

a five-sigma value of σ

_min is about 60 meters;

a five-sigma value of σ

_max is about 700 meters;

α

_min is 2 dBWatts/dBMeters; and

α

_max is 6 dBWatts/dBMeters.

15. A method for estimating the position of a Wi-Fi enabled device using qualitative data related to one or more characteristics of a Wi-Fi access point'"'"'s signal coverage area, the method comprising:

one or more signals transmitted by the Wi-Fi access points;

identifying the Wi-Fi access points;

retrieving previously calculated locations of the Wi-Fi access points and previously calculated weights assigned to the Wi-Fi access points from a reference database, where the weights correspond to characteristics of each Wi-Fi access point'"'"'s coverage area, including a plurality of measured power values for each access point; and

using the calculated locations and the calculated weights to estimate the position of the Wi-Fi enabled device,

wherein Wi-Fi access points having relatively small coverage areas are assigned a higher effective weight than Wi-Fi access points having relatively large coverage areas and the position estimate of the Wi-Fi enabled device will be biased to rely more heavily rely on signals detected from the Wi-Fi access points with relatively smaller coverage areas, even if said signals are detected with relatively weaker power than signals detected from Wi-Fi access points with larger coverage areas and relatively higher power.

16. The method of claim 15, wherein at least one of the Wi-Fi access points has a radius of coverage, the radius of coverage having at least one section, each section having corresponding weights, where the weights correspond to characteristics of the Wi-Fi access point'"'"'s coverage area.

17. A method of characterizing Wi-Fi access points in order to increase the accuracy of position, velocity and bearing estimation techniques based on signals received from those access points by classifying the Wi-Fi access points based on coverage areas of the Wi-Fi signals emitted by the Wi-Fi access points, the method of characterizing comprising:

measuring a series of Wi-Fi signals of each Wi-Fi access point;

determining a coverage area of each Wi-Fi access point based on its corresponding series of signals; and

assigning a weight to each Wi-Fi access point based on the coverage areas in which Wi-Fi access points having relatively small coverage areas are assigned a higher effective weight than Wi-Fi access points having relatively large coverage areas,

wherein position, velocity, and bearing estimation techniques will bias their estimates of position, velocity, and bearing to more heavily rely on signals detected from the Wi-Fi access points with relatively smaller coverage areas, even if said signals are detected with relatively weaker power than signals detected from Wi-Fi access points with larger coverage areas and relatively higher power.

18. The method of claim 17, wherein determining the coverage area comprises:

calculating a plurality of distances corresponding to each received signal within the coverage area of the Wi-Fi access point, the distances being measured from the associated position relative to the Wi-Fi access point; and

determining an average radius of coverage of the Wi-Fi access point based on the plurality of distances from the access point.

19. The method of claim 18, wherein determining the coverage area comprises:

determining the standard deviation of the coverage area in the Wi-Fi access point based on the plurality of distances.

20. The method of claim 18 further comprising:

determining a differential of a power value in dB of the received signal and the distance in dB from the Wi-Fi access point at each of the plurality of distances.

22. The method of claim 17, wherein the weight of the Wi-Fi access point is assigned using a power-distance gradient of the Wi-Fi access point, wherein a larger power-distance gradient corresponds to a higher weight and a smaller power-distance gradient corresponds to a smaller weight.

23. The method of claim 17, further comprising:

dividing the coverage area into a plurality of sections based on the series of signals and

assigning a weight to each of the plurality of sections,

wherein the weight is used as a characteristic of the section in the position, velocity, and bearing estimation techniques.

21. A method of characterizing Wi-Fi access points in order to increase the accuracy of position, velocity and bearing estimation techniques based on signals received from those access points by classifying the Wi-Fi access points based on coverage areas of the Wi-Fi signals emitted by the Wi-Fi access points, the method of characterizing comprising:

measuring a series of power values of the Wi-Fi signal of the Wi-Fi access point at a plurality of distances from the Wi-Fi access point;

determining a coverage area of the Wi-Fi access point based on the series of power values at the plurality of distances; and

assigning a weight to the Wi-Fi access point based on the coverage area,

wherein the weight of the Wi-Fi access point is assigned using the differential of the power in dB and the distance in dB from the Wi-Fi access point, wherein a larger differential corresponds to a higher weight and a smaller differential corresponds to a smaller weight, so that position, velocity, and bearing estimation techniques will bias their estimates of position, velocity, and bearing to more heavily rely on signals detected from the Wi-Fi access points with a relatively larger differential.