Probabilistic estimation of location based on wireless signal strength and platform profiles

• US 8,706,142 B1
• Filed: 08/20/2012
• Issued: 04/22/2014
• Est. Priority Date: 08/18/2011
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Mishra, Arunesh
• Primary Examiner(s): SHEDRICK, CHARLES TERRELL
• Application Number:
  US13/589,753
• Time in Patent Office: 610 Days
• Field of Search: 455/456.1, 455/456.5, 455/456.6
• US Class Current: 455/456.3
• CPC Class Codes: G01S 5/0249 Determining position using measurements made by a non-stationary device other than the device whose position is being determined
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence
• CPC Class Codes: H04W 64/003 locating network equipment

Abstract

According to an embodiment, a method of estimating a location of an access point is provided. The method includes storing a first and a second sample respectively received from a first and a second mobile device, both samples including a location of their respective mobile devices, an access point identifier from the access point, and a value corresponding to a signal strength of a signal from the access point measured at their respective mobile device. A first and second platform profile is selected based on characteristics of the respective first and second mobile devices. The cells of a matrix are populated with probabilities based on mobile device locations, the signal strength values and platform profiles based on platform profiles associated with mobile devices. Finally, the location of the access point is estimated based on the matrix.

Claims

1. A method of estimating a location of a wireless access point, comprising:

storing a first sample received from a first mobile device, the first sample including a first mobile device location, an access point identifier from the wireless access point, and a first value corresponding to a signal strength of a signal from the wireless access point;

selecting a first platform profile based on characteristics of the first mobile device;

populating cells of a matrix with probabilities based on the first mobile device location, the first platform profile and the first value;

storing a second sample received from a second mobile device, the second sample including a second mobile device location, an access point identifier from the wireless access point, and a second value corresponding to a signal strength of a signal from the wireless access point;

selecting a second platform profile based on characteristics of the second mobile device;

updating the probabilities in the matrix based on the second mobile device location, the second platform profile and the second value; and

estimating the location of the wireless access point based on the matrix.

2. The method of claim 1, wherein selecting the first platform profile based on characteristics of the first mobile device comprises selecting a platform profile that includes multiple probability distribution functions, each function corresponding to a different signal strength and the first mobile device.

3. The method of claim 2, wherein selecting the first platform profile comprises selecting a platform profile that includes multiple probability distribution functions, wherein each probability function produces a probability that a signal source measured by the first mobile device can be found at a distance.

4. The method of claim 1, wherein estimating the location of the wireless access point comprises estimating the location of the wireless access point based on at least two determined probabilities, each probability associated with a different mobile device.

5. The method of claim 4, further comprising for at least two probabilities in the matrix:

analyzing the at least two probabilities; and

modifying each of the at least two probabilities based on the analyzing of the probabilities.

6. The method of claim 5, wherein analyzing the probabilities comprises, for each probability, determining a minimum probability, a maximum probability and a sum of the at least two probabilities.

7. The method of claim 1, further comprising for a sample, determining a location for another wireless access point based on an access point identifier;

and estimating a distance value for the stored first sample based on the determined another access point location and the first mobile device location value of the sample.

8. The method of claim 1, wherein storing a plurality of samples received from a plurality of sampled mobile devices comprises storing a sample that includes a mobile device location determined by using a global positioning system determination.

9. The method of claim 1, wherein storing a plurality of samples received from a plurality of sampled mobile devices comprises storing a sample that includes a mobile device location determined by using a known access point location.

10. The method of claim 1, further comprising determining the first platform profile based on the stored samples associated with the first mobile device.

11. The method of claim 10, wherein determining the first platform profile based on the stored samples comprises determining a platform profile that uses the stored samples to model a signal strength characteristic of the first mobile device.

12. A location estimator, comprising:

a sample collector configured to store a plurality of samples received from a plurality of sampled mobile devices, each sample including a mobile device location, an access point location, and a signal strength; and

a probability determiner configured to determine a probability that a mobile device is a distance from an access point based on

a value corresponding to the signal strength of the signal received at the mobile device from the access point,

a stored sample, wherein the access point is associated with the stored sample, and

a first platform profile based on a signal characteristic of the type and implementation of the mobile device,

wherein the location estimator is configured to estimate the location of the mobile device based on the probability.

13. The location estimator of claim 12, wherein the location estimator is configured to estimate location based on at least two determined probabilities, each probability being:

determined by the probability determiner, and

associated with a different access point.

14. The location estimator of claim 13, further comprising

a probability analyzer configured to analyze the at least two determined probabilities;

and

a probability modifier configured to modify each of the at least two determined probabilities based on the analyzing of the probabilities.

15. The location estimator of claim 14, wherein analyzing, by the probability analyzer, of the probabilities comprises, determining a minimum probability, a maximum probability and a sum of the at least two probabilities.

16. The location estimator of claim 12, further comprising a distance estimator configured to estimate a distance for a stored sample based on the access point location and the mobile device location values of the sample.

17. The location estimator of claim 12, wherein the sample collector is configured to store a sample having a mobile device location determined by using a global positioning system determination.

18. A non-transitory computer readable storage medium having computer-executable instructions stored thereon that, when executed by a computing device, cause the computing device to perform a method of estimating a location of a mobile device, the method comprising:

storing a first sample received from a first mobile device, the first sample including a first mobile device location, an access point identifier from the wireless access point, and a first value corresponding to a signal strength of a signal from the wireless access point;

selecting a first platform profile based on characteristics of the first mobile device;

populating cells of a matrix with probabilities based on the first mobile device location, the first platform profile and the first value;

storing a second sample received from a second mobile device, the second sample including a second mobile device location, an access point identifier from the wireless access point, and a second value corresponding to a signal strength of a signal from the wireless access point;

selecting a second platform profile based on characteristics of the second mobile device;

updating the probabilities in the matrix based on the second mobile device location, the second platform profile and the second value; and

estimating the location of the wireless access point based on the matrix.