Device position estimates from motion and ambient light classifiers

Patent metadata

Field	Value
Publication number	US-9366749-B2
Application number	US-201213348497-A
Country	US
Kind code	B2
Filing date	Jan 11, 2012
Priority date	Apr 15, 2011
Publication date	Jun 14, 2016
Grant date	Jun 14, 2016

Abstract

A position estimate for a mobile device is generated using data from motion sensors, such as accelerometers, magnetometers, and/or gyroscopes, and data from light sensors, such as an ambient light sensor, proximity sensor and/or camera intensity sensor. A plurality of proposed positions with associated likelihoods is generated by analyzing information from the motion sensors and a list of candidate positions is produced based on information from the light sensors. At least one of the plurality of proposed positions is eliminated using the list of candidate positions and a position estimate for the mobile device is determined based on the remaining proposed positions and associated likelihoods. The proposed positions may be generated by extracting features from the information from the motion sensors and using models to generate likelihoods for the proposed positions. The likelihoods may be filtered over time. Additionally, a confidence metric may be generated for the estimated position.

First claim

What is claimed is:

1. A method of determining a position estimate of a mobile device with respect to a user, comprising:
receiving signals from at least one motion sensor in the mobile device;
analyzing the signals from the at least one motion sensor in the mobile device to generate a plurality of proposed positions with respect to the user with associated likelihoods;
receiving signals from at least one light sensor in the mobile device;
processing the signals from the at least one light sensor in the mobile device to produce a list of candidate positions;
eliminating at least one of the plurality of proposed positions using the list of candidate positions; and
determining the position estimate for the mobile device with respect to the user based on remaining proposed positions and associated likelihoods.

2. The method of claim 1 , wherein eliminating at least one of the plurality of proposed positions using the list of candidate positions comprises eliminating any proposed position that is not included in the list of candidate positions.

3. The method of claim 1 , wherein the at least one motion sensor comprises at least one of accelerometers, magnetometers, and gyroscopes.

4. The method of claim 1 , wherein the at least one light sensor comprises at least one of an ambient light sensor, proximity sensor and camera intensity sensor.

5. The method of claim 1 , wherein analyzing the signals from the at least one motion sensor in the mobile device to generate the plurality of proposed positions with associated likelihoods comprises:
extracting features from the signals from the at least one motion sensor;
accessing models of features; and
using the features and the models of features to generate likelihoods for each of the plurality of proposed positions.

6. The method of claim 5 , further comprising filtering the plurality of proposed positions with associated likelihoods over time.

7. The method of claim 1 , further comprising generating a confidence metric associated with the position estimate.

8. The method of claim 7 , wherein the confidence metric is generated based on a difference of likelihoods of two most likely proposed positions after eliminating the at least one of the plurality of proposed positions using the list of candidate positions.

9. The method of claim 1 , further comprising generating likelihoods that are associated with candidate positions in the list of candidate positions, wherein eliminating at least one of the plurality of proposed positions using the list of candidate positions comprises multiplying the likelihoods associated with each of the plurality of proposed positions with the likelihoods associated with the candidate positions to determine a proposed position with a highest combined likelihood level that is used as the position estimate.

10. The method of claim 1 , wherein processing the signals from the at least one light sensor to produce the list of candidate positions is performed prior to generating the plurality of proposed positions with associated likelihoods.

11. A mobile device comprising:
at least one motion sensor;
at least one light sensor;
memory; and
a processor coupled to the memory and coupled to receive signals from the at least one motion sensor and coupled to receive signals from the at least one light sensor, the processor being configured to analyze the signals from the at least one motion sensor to generate a plurality of proposed positions with respect to a user with associated likelihoods, process the signals from the at least one light sensor to produce a list of candidate positions, eliminate at least one of the plurality of proposed positions using the list of candidate positions, determine a position estimate for the mobile device with respect to the user based on remaining proposed positions and associated likelihoods, and store the position estimate in the memory.

12. The mobile device of claim 11 , wherein the processor is configured to eliminate at least one of the plurality of proposed positions using the list of candidate positions by being configured to eliminate any proposed position that is not included in the list of candidate positions.

13. The mobile device of claim 11 , wherein the at least one motion sensor comprises at least one of accelerometers, magnetometers, and gyroscopes.

14. The mobile device of claim 11 , wherein the at least one light sensor comprises at least one of an ambient light sensor, proximity sensor and camera intensity sensor.

15. The mobile device of claim 11 , wherein the processor is configured to analyze the signals from the at least one motion sensor to generate the plurality of proposed positions with associated likelihoods by being configured to:
extract features from the signals from the at least one motion sensor;
access models of features; and
use the features and the models of features to generate likelihoods for each of the plurality of proposed positions.

16. The mobile device of claim 15 , wherein the processor is further configured to filter the plurality of proposed positions with associated likelihoods over time.

17. The mobile device of claim 11 , wherein the processor is further configured to generate a confidence metric associated with the position estimate.

18. The mobile device of claim 17 , wherein the processor is configured to generate the confidence metric based on a difference of likelihoods of two most likely proposed positions after eliminating the at least one of the plurality of proposed positions using the list of candidate positions.

19. The mobile device of claim 11 , wherein the processor is further configured to generate likelihoods that are associated with candidate positions in the list of candidate positions, wherein the processor is configured to eliminate at least one of the plurality of proposed positions using the list of candidate positions by being configured to multiply the likelihoods associated with each of the plurality of proposed positions with the likelihoods associated with the candidate positions to determine a proposed position with a highest combined likelihood level that is used as the position estimate.

20. The mobile device of claim 11 , wherein the processor is configured to produce the list of candidate positions before generating the plurality of proposed positions with associated likelihoods.

21. A mobile device comprising:
means for receiving signals from at least one motion sensor in the mobile device;
means for analyzing the signals from the at least one motion sensor in the mobile device to generate a plurality of proposed positions with respect to a user with associated likelihoods;
means for receiving signals from at least one light sensor in the mobile device;
means for processing the signals from the least one light sensor in the mobile device to produce a list of candidate positions;
means for eliminating at least one of the plurality of proposed positions using the list of candidate positions; and
means for determining a position estimate for the mobile device with respect to the user based on remaining proposed positions and associated likelihoods.

22. The mobile device of claim 21 , wherein the means for eliminating at least one of the plurality of proposed positions using the list of candidate positions comprises means for eliminating any proposed position that is not included in the list of candidate positions.

23. The mobile device of claim 21 , wherein the at le

Assignees

• Grokop Leonard Henry
• Narayanan Vidya
• Qualcomm Inc

Inventors

• Grokop Leonard Henry
• Narayanan Vidya

Classifications

• G01C21/1656

  with passive imaging devices, e.g. cameras · CPC title

• G06F1/1686

  the I/O peripheral being an integrated camera · CPC title

• G01C19/44

  for indicating the vertical · CPC title

• H04M1/72522

  Electricity · mapped topic

• G01S5/16 Primary

  using electromagnetic waves other than radio waves · CPC title