SYSTEM AND METHOD FOR PROBABLISTIC WLAN POSITIONING

• US 20130163448A1
• Filed: 12/22/2011
• Published: 06/27/2013
• Est. Priority Date: 12/22/2011
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm Atheros Incorporated (Qualcomm, Inc.)
• Inventors: Ruuska, Vesa V.
• Granted Patent: US 8,797,899 B2
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence

Abstract

This disclosure is directed to a wireless network node having position determination capabilities. The position of a node is determined using range measurements to other network nodes having known locations. Probability density functions modeling uncertainty factors are incorporated in the estimation algorithms to account for the dynamic nature of wireless network, including the relative motion of a node in the network. These probabilistic estimation techniques provide a solution in the form of an expectation value for the position of the network node and a variance that can be assessed to determine the validity of the position determination.

Claims

1. A method for making a position determination for a first node within a wireless network comprising the steps of:

a) obtaining position information for a plurality of known network nodes;

b) obtaining range measurements for distances between the first node and the plurality of known network nodes;

c) determining a single range measurement probability density function for a position of the first network node for each of the range measurements;

d) determining a combined probability density function by taking the product of the singe range measurement probability density functions; and

e) determining an expectation value corresponding to the first network node'"'"'s position and a variance of the expectation value by integrating with respect to the combined probability density function.

2. The method of claim 1, wherein the step of determining a single range measurement probability density function for a position of the first network node for each of the range measurements comprises modeling an uncertainty factor selected from the group consisting of process noise, known network node location and range measurement.

3. The method of claim 2, wherein the step of determining a single range measurement probability density function for a position of the first network node for each of the range measurements comprises modeling uncertainty factors for process noise and known network node location.

4. The method of claim 3, wherein the probability density functions modeling uncertainty factors for process noise and known network node location comprise Gaussian distributions.

5. The method of claim 1, wherein integrating with respect to the combined probability density function comprises performing a lattice point integration.

6. The method of claim 1, wherein integrating with respect to the combined probability density function comprises perfol ming a Gauss-Hermite quadrature calculation.

7. The method of claim 1, further comprising the step of assessing the variance of the expectation value to determine the validity of the position determination for the first network node.

8. The method of claim 1, wherein the step of obtaining range measurements for distances between the first node and the plurality of known network nodes comprises performing a round trip time calculation.

9. The method of claim 1, wherein the step of obtaining range measurements for distances between the first node and the plurality of known network nodes comprises taking at least one non-simultaneous measurement.

10. The method of claim 1, further comprising the step of supplementing the position determination resulting from the integration of the combined range measurement probability density functions with position information from an independent source.

11. A wireless network having position determination capabilities comprising a first network node, a plurality of network nodes having known location and a probabilistic positioning engine configured to:

a) obtain position information for the plurality of known network nodes;

b) obtain range measurements for distances between the first node and the plurality of known network nodes;

c) determine a single range measurement probability density function for a position of the first network node for each of the range measurements;

d) determine a combined probability density function by taking the product of the singe range measurement probability density functions; and

e) calculate a position determination comprising an expectation value corresponding to the first network node'"'"'s position and a variance of the expectation value by integrating with respect to the combined probability density function.

12. The wireless network of claim 11, wherein the probabilistic positioning engine is configured to determine a single range measurement probability density function for a position of the first network node for each of the range measurements by modeling an uncertainty factor selected from the group consisting of process noise, known network node location and range measurement.

13. The wireless network of claim 12, wherein the probabilistic positioning engine is configured to determine a single range measurement probability density function for a position of the first network node for each of the range measurements by modeling uncertainty factors for process noise and known network node location.

14. The wireless network of claim 13, wherein the probability density functions modeling uncertainty factors for process noise and known network node location comprise Gaussian distributions.

15. The wireless network of claim 11, wherein the probabilistic positioning engine is configured to integrate with respect to the combined probability density function by performing a lattice point integration.

16. The wireless network of claim 11, wherein the probabilistic positioning engine is configured to integrate with respect to the combined probability density function by performing a Gauss-Hermite quadrature calculation.

17. The wireless network of claim 11, wherein the probabilistic positioning engine is further configured to assess the variance of the expectation value to determine the validity of the position determination for the first network node.

18. The wireless network of claim 11, wherein the probabilistic positioning engine is configured to obtain range measurements for distances between the first node and the plurality of known network nodes by performing a round trip time calculation.

19. The wireless network of claim 11, wherein the probabilistic positioning engine is configured to obtain range measurements for distances between the first node and the plurality of known network nodes by taking at least one non-simultaneous measurement.

20. The wireless network of claim 11, wherein the probabilistic positioning engine is further configured to supplement the position determination resulting from the integration of the combined range measurement probability density functions with position information from an independent source.