METHOD FOR SEAMLESS TRANSITION FROM URBAN OUTDOOR ENVIRONMENTS TO INDOOR NAVIGATION

• US 20130065604A1
• Filed: 09/13/2011
• Published: 03/14/2013
• Est. Priority Date: 09/13/2011
• Status: Abandoned Application

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Werner, Benjamin A., Garin, Lionel Jacques, Raman, Sundar
• Application Number:
  US13/231,902
• Publication Number:
  US 20130065604A1
• Time in Patent Office: Days
• US Class Current: 455/456.1
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence

Abstract

Techniques are disclosed for managing operation of multiple estimators in a wireless device. In at least one implementation, techniques for providing relatively seamless transition between dissimilar regions of a state space may be provided.

Claims

1. A machine implemented method comprising:

calculating probabilities of multiple position estimators associated with a mobile device;

sampling beliefs of said multiple position estimators based, at least in part, on said probabilities to generate first samples; and

updating a combined belief for said multiple positioning estimators based, at least in part, on said first samples.

2. The method of claim 1, wherein:

said calculating probabilities of said multiple position estimators associated with said mobile device includes calculating a probability that a first estimator'"'"'s belief and measurement model corroborate observed measurements.

3. The method of claim 1, further comprising:

propagating said beliefs of said multiple position estimators forward in time to compensate for elapsed times between measurements before calculating said probabilities.

4. The method of claim 3, further comprising:

sampling said beliefs of said multiple position estimators after said propagating to generate second samples; and

determining whether to activate a new estimator based, at least in part, on said second samples.

5. The method of claim 1, further comprising:

determining whether to deactivate a first estimator of said multiple position estimators based, at least in part, on a corresponding one of said probabilities.

6. The method of claim 5, wherein:

said determining whether to deactivate said first estimator includes determining to deactivate said first estimator if said corresponding one of said probabilities is below a threshold value.

7. The method of claim 1, wherein:

calculating probabilities of said multiple position estimators further includes calculating probabilities that sum to approximately one.

8. The method of claim 1, wherein:

said calculating probabilities of said multiple position estimators includes using an expression;

9. The method of claim 8, wherein:

said calculating probabilities of said multiple position estimators includes using an expression;

p(y_k|e_r)=∫

p(y_k|x_k, e_r)p(x_k)dx_k

where p(y_k|x_k, e_r) is a measurement model of estimator e_r and p(x_k) is a belief of estimator e_r.

10. The method of claim 1, wherein at least one of said position estimators is based, at least in part, on a Kalman filter.

11. The method of claim 1, wherein at least one of said position estimators is based, at least in part, on a particle filter.

12. An apparatus comprising:

one or more sensors to obtain measurements; and

a processor to;

initialize a combined belief for active estimators of a plurality of position estimators based, at least in part, on said measurements;

calculate probabilities of said active estimators;

sample beliefs of said active estimators based, at least in part, on said probabilities to generate samples; and

update said combined belief for said active estimators based, at least in part, on said first samples.

13. The apparatus of claim 12, wherein:

said probabilities of said active estimators include probabilities that beliefs and measurement models of individual estimators corroborate observed measurements.

14. The apparatus of claim 12, wherein the processor is further to propagate said active estimators forward in time to compensate for elapsed times between measurements before said probabilities are calculated.

15. The apparatus of claim 14, wherein the processor is further to:

sample said beliefs of said active estimators after said beliefs have been propagated forward in time to generate second samples; and

determine whether to activate an inactive estimator in said plurality of position estimators based, at least in part, on said second samples.

16. The apparatus of claim 12, wherein the processor is further to determine whether to deactivate a first active estimator in said plurality of position estimators based, at least in part, on a corresponding calculated probability.

17. The apparatus of claim 12, wherein:

said probabilities of said active estimators calculated by said estimation manager sum to approximately one.

18. The apparatus of claim 12, wherein the processor is further to use the following expression to calculate said probabilities of said active estimators:

19. The apparatus of claim 18, wherein:

said estimation manager is further to use the following expression to calculate said probabilities of said active estimators;

p(y_k|e_r)=∫

p(y_k|x_k, e_r)p(x_k)dx_k

where p(y_k|x_k, e_r) is a measurement model of estimator e_r and p(x_k) is a belief of estimator e_r.

20. An article comprising:

a non-transitory storage medium comprising machine-readable instructions stored thereon which are executable by a special purpose computing apparatus to;

calculate probabilities of multiple position estimators associated with a mobile device;

sample beliefs of said multiple position estimators based, at least in part, on said probabilities to generate first samples; and

update a combined belief for said multiple positioning estimators based, at least in part, on said first samples.

21. The article of claim 20, wherein said instructions are further executable by said special purpose computing apparatus to:

propagate said beliefs of said multiple position estimators forward in time to compensate for elapsed times between measurements before calculating said probabilities.

22. The article of claim 21, wherein said instructions are further executable by said special purpose computing apparatus to:

sample said beliefs of said multiple position estimators after said propagating to generate second samples; and

determine whether to activate a new estimator based, at least in part, on said second samples.

23. The article of claim 20, wherein said instructions are further executable by said special purpose computing apparatus to:

determine whether to deactivate a first estimator of said multiple position estimators based, at least in part, on a corresponding one of said probabilities.

24. The article of claim 23, wherein said instructions are further executable by said special purpose computing apparatus to:

determine whether to deactivate said first estimator by determining to deactivate said first estimator if said corresponding one of said probabilities is below a threshold value.

25. An apparatus comprising:

means for calculating probabilities of multiple position estimators associated with a mobile device;

means for sampling beliefs of said multiple position estimators based, at least in part, on said probabilities to generate first samples; and

means for updating a combined belief for said multiple positioning estimators based, at least in part, on said first samples.

26. A method comprising, at a mobile device:

defining multiple operating regions of said mobile device, said mobile device being capable of acquiring satellite positioning system (SPS) signals in at least a first region, acquiring indoor navigation signals in at least a second region;

applying a first estimator to process acquired SPS signals while operating in said first region and applying a second estimator to process acquired indoor navigation signals while operating in said second region; and

combining results from said first and second estimators for estimating or predicting a navigation state of said mobile device while said mobile device is in a region overlapping said first and second regions.

27. The method of claim 26, wherein said first estimator comprises application of a Kalman filter to pseudorange measurements obtained from acquisition of SPS signals.

28. The method of claim 27, wherein said second estimator comprises application of a particle filter to measured characteristics of acquired indoor navigation signals.

29. The method of claim 26, and further comprising:

continuing application of said first and second estimators for estimating or predicting said navigation state while in said overlapping region; and

discontinuing application of said first estimator responsive to a confidence indicator associated with said first estimator.

30. The method of claim 29, wherein said confidence indicator is determined based, at least in part, on a computed likelihood that said first estimator is producing reliable solutions.

31. The method of claim 26, wherein said acquired indoor navigation signals comprise signals transmitted from a wireless local area network.

32. The method of claim 26, and further comprising applying said second estimator to measurements obtained from one or more inertial sensors.

33. The method of claim 26, wherein said combining results further comprises combining results from one or more additional estimators with said results from said first and second estimators for estimating or predicting the navigation state.

34. An apparatus comprising:

a receiver to acquire satellite positioning system (SPS) signals and indoor navigation signals; and

a processor to;

define multiple operating regions of a mobile device including a first region where said mobile device is capable of acquiring satellite positioning system (SPS) and a second region where said mobile device is capable of acquiring indoor navigation signals;

apply a first estimator to process said acquired SPS signals while said mobile device is operating in said first region and apply a second estimator to process said acquired indoor navigation signals while said mobile device is operating in said second region; and

combine results from said first and second estimators for estimating or predicting a navigation state of said mobile device while said mobile device is in a region overlapping said first and second regions.

35. The apparatus of claim 34, and further comprising one or more inertial sensors, and wherein said processor is further to:

apply said second estimator to measurements obtained from said one or more inertial sensors.

36. An article comprising:

a non-transitory storage medium comprising machine-readable instructions stored thereon which are executable by a special purpose computing apparatus to;

define multiple operating regions of a mobile device including a first region where said mobile device is capable of acquiring satellite positioning system (SPS) and a second region where said mobile device is capable of acquiring indoor navigation signals;

apply a first estimator to process said acquired SPS signals while said mobile device is operating in said first region and apply a second estimator to process said acquired indoor navigation signals while said mobile device is operating in said second region; and

combine results from said first and second estimators for estimating or predicting a navigation state of said mobile device while said mobile device is in a region overlapping said first and second regions.

37. An apparatus comprising:

means for defining multiple operating regions of said mobile device, said mobile device being capable of acquiring satellite positioning system (SPS) signals in at least a first region, acquiring indoor navigation signals in at least a second region;

means for applying a first estimator to process acquired SPS signals while operating in said first region and applying a second estimator to process acquired indoor navigation signals while operating in said second region; and

means for combining results from said first and second estimators for estimating or predicting a navigation state of said mobile device while said mobile device is in a region overlapping said first and second regions.