Location Determination

• US 20090286549A1
• Filed: 05/16/2008
• Published: 11/19/2009
• Est. Priority Date: 05/16/2008
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Canon, Stephen Tyrone, Sazegari, Ali
• Granted Patent: US 8,644,843 B2
• Time in Patent Office: Days
• US Class Current: 455/456.100
• CPC Class Codes: G01S 5/02524 Creating or updating the radio-map
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Systems, methods, and computer program products obtain power information indicating a detected power of respective signals received in a mobile device from multiple transmitters. Using at least the obtained power information, respective probability values for a plurality of positions are determined, each probability value indicating a probability that the mobile device is in a corresponding position. An estimated position of the mobile device is identified based at least in part on the determined probability values.

Claims

1. A method comprising:

obtaining power information indicating a detected power of respective signals received in a mobile device from multiple transmitters;

determining, using at least the obtained power information, respective probability values for a plurality of positions, each probability value indicating a probability that the mobile device is in a corresponding position; and

identifying an estimated position of the mobile device based at least in part on the determined probability values.

2. The method of claim 1, wherein determining the probability values and identifying the estimated position comprise:

generating a statistical model based at least in part on the obtained power information;

selecting a geographical region to which the generated statistical model applies; and

randomly or pseudo randomly selecting a plurality of positions within the selected geographical region, wherein each of the probability values is identified as being associated with a corresponding one of the plurality of positions.

3. The method of claim 2, further comprising:

determining that a previous location of the mobile device has been registered,

wherein the geographical region is selected taking into account the registered previous location.

4. The method of claim 2, further comprising:

determining a first transmitter, among the multiple transmitters, having a strongest signal according to the obtained power information,

wherein the geographical region is selected taking into account a location of the determined first transmitter.

5. The method of claim 2, wherein multiple previous location determinations have been performed, the method further comprising:

generating an error estimate for a most recent of the previous location determinations,

wherein the geographical region is selected taking into account the generated error estimate.

6. The method of claim 2, wherein the statistical model is configured to have at least one term added and be taken into account in determining the probability values.

7. The method of claim 6, further comprising:

for each of the multiple transmitters, adding a term to the statistical model, the term reflecting that a conditional probability that the mobile device is a distance d from the respective transmitter follows a log-normal distribution, wherein a mean and a standard deviation of the log-normal distribution are functions of the power of the respective transmitter.

8. The method of claim 7, further comprising:

obtaining a training data set comprising signal strength information regarding known locations; and

estimating the functions for the mean and the standard deviation using the obtained training data set.

9. The method of claim 6, further comprising:

for each pair of the multiple transmitters, adding a term to the statistical model, the term reflecting that a conditional probability that the mobile device is at a distance d from a point on a line joining the pair of the multiple transmitters follows a log-normal distribution, wherein a mean and a standard deviation are functions of the powers of the respective two transmitters.

10. The method of claim 9, further comprising:

obtaining a training data set comprising signal strength information regarding known locations; and

estimating the functions for the mean and the standard deviation using the obtained training data set.

11. The method of claim 6, further comprising:

obtaining a previously estimated location for the mobile device; and

adding a term to the statistical model, the term reflecting that a conditional probability that the mobile device is at a distance d from the previously estimated location follows a radially symmetric Gaussian distribution about the previously estimated location.

12. The method of claim 11, wherein a standard deviation of the radially symmetric Gaussian distribution is based on an error estimate and on information about how recently the previously estimated location was identified.

13. The method of claim 6, further comprising:

obtaining geographical information relating to at least one of the plurality of positions; and

adding a term to the statistical model based on the obtained geographical information.

14. The method of claim 13, wherein the geographical information provides a bias toward some locations over other locations.

15. The method of claim 1, wherein identifying the estimated position comprises:

selecting one of the determined probability values that is associated with a highest probability that the mobile device is in the corresponding position.

16. The method of claim 1, wherein identifying the estimated position comprises:

determining a centroid location based on the determined probability values; and

selecting the determined centroid location as the estimated position.

17. The method of claim 1, further comprising:

determining that additional power information is required to identify the estimated position;

postponing the identification of the estimated position for a period of time; and

collecting the additional power information, wherein the estimated position of the mobile device is identified based also on the additional power information.

18. A computer program product, encoded on a tangible program carrier, operable to cause a portable device to perform operations comprising:

obtaining power information indicating a detected power of respective signals received in a mobile device from multiple transmitters;

determining, using at least the obtained power information, respective probability values for a plurality of positions, each probability value indicating a probability that the mobile device is in the corresponding position; and

identifying an estimated position of the mobile device based at least in part on the determined probability values.

19. A mobile device comprising:

a processor-accessible medium containing power information that indicates a detected power of respective signals received in a mobile device from multiple transmitters; and

a position estimator that

     1) determines, using at least the obtained power information, respective probability values for a plurality of positions, each probability value indicating a probability that the mobile device is in the corresponding position; and

     2) identifies an estimated position of the mobile device based at least in part on the determined probability values.