Constraining inertial navigation system solution according to pedometrical data

• US 9,226,113 B2
• Filed: 12/16/2011
• Issued: 12/29/2015
• Est. Priority Date: 12/16/2011
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Amizur, Yuval, Banin, Leor
• Primary Examiner(s): Mizrahi, Diane
• Application Number:
  US13/977,045
• Publication Number:
  US 20140194138A1
• Time in Patent Office: 1,474 Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/024 Guidance services

Abstract

Described herein are techniques related to constraining Inertial Navigation System (INS) solution according to pedometrical data. Data from sensors external to an inertial navigation module are leveraged in computing the final solution for indoor navigation. The techniques render the drift and divergence in inertial sensors to be much slower. Additionally, the techniques are not dependent on the attitude of the mobile device used for indoor navigation relative to the user'"'"'s body.

Claims

1. A method comprising:

receiving, by a processing unit of a processing device of a mobile device, a first signal representative of inertial navigation data from an inertial navigation module, wherein the inertial navigation module utilizes one or more sensors physically located with a user;

receiving, by the processing unit of the processing device of the mobile device, a second signal representative of pedometrical data from a pedometer, wherein the pedometer utilizes the one or more sensors physically located with the user;

generating, by the processing unit of the processing device of the mobile device, a correction signal using the first and second signals; and

generating, by the processing unit of the processing device of the mobile device, a final solution signal by Kalman filtering or Bayesian filtering the first and second signals.

2. A method as recited in claim 1, wherein the first signal representative of inertial navigation data is generated by the inertial navigation module using one or more motion equations, and wherein generating the correction signal and the final solution signal using the first and second signals comprises Kalman filtering the first and second signals to provide the correction signal and the final solution signal.

3. A method as recited in claim 1, wherein the first signal representative of inertial navigation data is generated by, the inertial navigation module using one or more motion equations, and wherein generating the correction signal and the final solution signal using the first and second signals comprises Bayesian filtering the first and second signals to provide the correction signal and the final solution signal.

4. A method as recited in claim 1 further comprising:

providing the correction signal to the inertial navigation module as input to the inertial navigation module such that the inertial navigation module outputs the first signal based at least in part on the correction signal.

5. A method as recited in claim 1 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof at the pedometer as input to the pedometer.

6. A method as recited in claim 1 further comprising:

providing the final solution signal to the pedometer as input to the pedometer such that the pedometer outputs the second signal based at least in part on the final solution signal.

7. A method as recited in claim 1 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof at the inertial navigation module as input to the inertial navigation module.

8. A method as recited in claim 1 further comprising:

receiving external source data from one or more external sources, wherein generating the correction signal and the final solution signal using the first and second signals comprises generating the correction signal and the final solution signal using the first signal, the second signal, and the external source data.

9. A method as recited in claim 8, wherein the external source data from the one or more external sources comprise one or more global navigation satellite system (GNSS) pseudo ranges, one or more Wi-Fi ranges, data related to a map, or a combination thereof.

10. A method as recited in claim 1 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof, wherein generating the correction signal and the final solution signal using the first and second signals comprises generating the correction signal and the final solution signal using the first signal, the second signal, and the sensor data.

11. A method comprising:

receiving, by a processing unit of a processing device of a mobile device, a first signal representative of inertial navigation data from an inertial navigation module, wherein the inertial navigation module utilizes one or more sensors physically located with a user;

receiving, by the processing unit of the processing device of the mobile device, a second signal representative of pedometrical data from a pedometer, wherein the pedometer utilizes the one or more sensors physically located with the user;

satellite system (GNSS) pseudo ranges, one or more Wi-Fi ranges, data related to a map, or a combination thereof.

12. A method as recited in claim 11 further comprising:

generating a correction signal based on the first and second signals; and

providing the correction signal to the inertial navigation module as input to the inertial navigation module such that the inertial navigation module outputs the first signal based at least in part on the correction signal.

13. A method as recited in claim 11 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof at the pedometer as input to the pedometer.

14. A method as recited in claim 11 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, a combination thereof at the inertial navigation module as input to the inertial navigation module.

15. A method as recited in claim 11 further comprising:

receiving external source data from one or more external sources, wherein generating the correction signal and the final solution signal using the first and second signals comprises generating the correction signal and the final solution signal using the first signal, the second signal, and the external source data.

16. A method as recited in claim 15, wherein the external source data from the one or more external sources comprise one or more global navigation satellite system (GNSS) pseudo ranges, one or more Wi-Fi ranges, data related to a map, or a combination thereof.

17. A method as recited in claim 11 further comprising:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof, wherein generating the final solution signal using the first signal comprises generating the final solution signal using the first signal and the sensor data.

18. A device comprising:

an inertial navigation module that outputs a first signal representative of inertial navigation data, wherein the inertial navigation module utilizes one or more sensors physically located with a user; and

a processing unit of a processing device of the device, the processing unit being coupled to receive the first signal and at least a second signal representative of pedometrical data, the processing unit further configured to generate a final solution signal by Kalman filtering or Bayesian filtering the first and second signals and a correction signal using the first signal and the second signal, the correction signal received by the inertial navigation module as an input signal.

19. A device as recited in claim 18, wherein the processing unit comprises a Kalman filter.

20. A device as recited in claim 18, wherein the processing unit comprises a Bayesian filter.

21. A device as recited in claim 18, wherein the processing unit further receives external source data from one or more external sources and generates the final solution signal and the correction signal using the first signal, the second signal, and the external source data.

22. A device as recited in claim 21, wherein the external source data from the one or more external sources comprise one or more global navigation satellite system (GNSS) pseudo ranges, one or more Wi-Fi ranges, data related to a map, or a combination thereof.

23. A device as recited in claim 18, wherein the processing unit further receives sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof and generates the final solution signal and the correction signal using the first signal, the second signal, and the sensor data.

24. A device as recited in claim 18, wherein the inertial navigation module outputs the first signal using one or more motion equations.

25. A device as recited in claim 18, wherein the inertial navigation module further receives sensor data from a gyroscope, an accelerometer, a compass, or a combination thereof and generates the first signal using the correction signal and the sensor data.

26. A device as recited in claim 18 further comprising:

a pedometer that outputs pedometrical data as the second signal.

27. A device as recited in claim 26, wherein the pedometer receives sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof and generates the second signal using the using the sensor data.

28. A device as recited in claim 26, wherein the pedometer receives the final solution signal as an input signal and generates the second signal using the final solution signal.

29. At least one computer accessible medium having stored thereon a set of instructions that, when executed by one or more processors, direct the one or more processors to execute operations comprising:

receiving a first signal representative of inertial navigation data from an inertial navigation module;

receiving a second signal representative of pedometrical data from a pedometer;

filtering the first and second signals through a Kalman filter or a Bayesian filter to provide a correction signal and a final solution signal; and

providing the correction signal to the inertial navigation module as input to the inertial navigation module such that the inertial navigation module outputs the first signal based at least in part on the correction signal.

30. At least one computer accessible medium as recited in claim 29, wherein the operations further comprise:

receiving external source data from one or more external sources, wherein the filtering comprises filtering the first signal, the second signal, and the external source data, and wherein the external source data from the one or more external sources comprise one or more global navigation satellite system (GNSS) pseudo ranges, one or more Wi-Fi ranges, data related to a map, or a combination thereof.

31. At least one computer accessible medium as recited in claim 29, wherein the operations further comprise:

receiving sensor data from a gyroscope, an accelerometer or a compass, or a combination thereof, wherein the filtering comprises filtering the first signal, the second signal, and the sensor data.