WI-FI ENHANCED TRACKING ALGORITHMS

• US 20130331121A1
• Filed: 06/12/2013
• Published: 12/12/2013
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Hakim, Daniel, Teolis, Carole, Bandyopadhyay, Amrit
• Granted Patent: US 9,297,658 B2
• Time in Patent Office: Days
• US Class Current: 455/456.1
• CPC Class Codes: G01C 21/12 executed aboard the object being navigated; Dead reckoning
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01S 5/013 Identifying areas in a building
• CPC Class Codes: G01S 5/0264 at least one of the systems being a non-radio wave positioning system
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Disclosed herein is the use of Wi-Fi based location estimates of a mobile device to provide global offset corrections (including automated initialization) and enhanced navigation accuracy through delivery of heading corrections. In an embodiment, dead reckoning tracking data may be received for a tracked subject. The tracking data includes a plurality of tracking points forming a tracking path of the tracked subject. A Wi-Fi position system location estimate is also obtained. The Wi-Fi position system location estimate is one of a plurality of Wi-Fi position system location estimates correlated to the dead reckoning tracking data. And a tracking related parameter is determined based on the correlation of the dead reckoning tracking data to the Wi-Fi position system location estimate.

Claims

1. A computer-implemented method of tracking a trackee, the method being implemented by a computer that includes a physical processor, the method comprising:

obtaining dead reckoning tracking data for a tracked subject, wherein the dead reckoning tracking data includes a plurality of tracking points forming a tracking path of the tracked subject;

obtaining a Wi-Fi position system location estimate that is one of a plurality of Wi-Fi position system location estimates that are correlated to the dead reckoning tracking data;

determining a tracking related parameter based on the correlation of the dead reckoning tracking data to the Wi-Fi position system location estimate.

2. The method of claim 1, wherein the tracking related parameter comprises at least one of:

a global offset, a rotation, a drift, or a scale.

3. The method of claim 1, further comprising

assigning a reliability number to the Wi-Fi position system location estimate;

and

using the reliability number to weight a contribution of the Wi-Fi position system location estimate to a solution of the tracking related parameter.

4. The method of claim 3, wherein the reliability number is based on at least one of

an error property of the Wi-Fi position system location estimate, or

a consistency with a motion model of the tracked subject.

5. The method of claim 3, further comprising:

performing path segmentation on the tracking path;

determining a shape that bounds the Wi-Fi position system location estimates;

refining segmentation of the tracking path based on the reliability numbers assigned to the plurality of Wi-Fi position system location estimates; and

performing shape matching on the refined path segmentation.

6. The method of claim 1, further comprising;

providing a corrected path based on the tracking related parameter.

7. The method of claim 1, wherein the dead reckoning tracking data is obtained from at least one an inertial sensor, and optical flow sensor, Doppler velocimeter, or wheel encoder.

8. A computing system comprising:

a dead reckoning sensor;

a processor communicatively connected with the dead reckoning sensor, the processor adapted to execute computer-readable instructions; and

a memory communicatively coupled to said processor, said memory having stored therein computer-readable instructions that, if executed by the processor, cause the processor to perform operations comprising;

obtaining dead reckoning tracking data for a tracked subject obtained from the dead reckoning sensor, wherein the dead reckoning tracking data includes a plurality of tracking points forming a tracking path of the tracked subject;

obtaining a Wi-Fi position system location estimate that is one of a plurality of Wi-Fi position system location estimates that are correlated to the dead reckoning tracking data;

determining a tracking related parameter based on the correlation of the dead reckoning tracking data to the Wi-Fi position system location estimate.

9. The computing system of claim 8, wherein the tracking related parameter comprises at least one of:

a global offset, a rotation, a drift, or a scale.

10. The computing system of claim 8, further comprising instructions, if executed by the processor, cause the processor to perform operations comprising:

assigning a reliability number to the Wi-Fi position system location estimate; and

using the reliability number to weight a contribution of the Wi-Fi position system location estimate to a solution of the tracking related parameter.

11. The computing system of claim 10, wherein the reliability number is based on at least one of

an error property of the Wi-Fi position system location estimate, or

a consistency with a motion model of the tracked subject.

12. The computing system of claim 10, further comprising instructions, if executed by the processor, causes the processor to perform operations comprising:

performing path segmentation on the tracking path;

determining a shape that bounds the Wi-Fi position system location estimates;

refining segmentation of the tracking path based on the reliability numbers assigned to the plurality of Wi-Fi position system location estimates; and

performing shape matching on the refined path segmentation.

13. The computing system of claim 8, further comprising instructions, if executed by the processor, cause the processor to perform operations comprising:

providing a corrected tracking path of the tracked subject based on the tracking related parameter.

14. The computing system claim 8, wherein the dead reckoning sensor is at least one an inertial sensor, and optical flow sensor, Doppler velocimeter, or wheel encoder.

15. A computer readable storage having stored therein computer-readable instructions that, if executed by a processor, cause the processor to perform operations comprising:

obtain dead reckoning tracking data for a tracked subject, wherein the dead reckoning tracking data includes a plurality of tracking points forming a tracking path of the tracked subject;

obtain a Wi-Fi position system location estimate that is one of a plurality of Wi-Fi position system location estimates that are correlated to the dead reckoning tracking data;

determine a tracking related parameter based on the correlation of the dead reckoning tracking data to the Wi-Fi position system location estimate.

16. The computer readable storage of claim 15, wherein the tracking related parameter comprises at least one of:

a global offset, a rotation, a drift, or a scale.

17. The computer readable storage of claim 15, further comprising instructions, if executed by the processor, causes the processor to perform operations comprising:

assign a reliability number to the Wi-Fi position system location estimate; and

use the reliability number to weight a contribution of the Wi-Fi position system location estimate to a solution of a tracking related parameter.

18. The computer readable storage of claim 17, wherein the reliability number is based on at least one of

an error property of the Wi-Fi position system location estimate, or

a consistency with a motion model of the tracked subject.

19. The computer readable storage of claim 17, further comprising instructions, if executed by the processor, causes the processor to perform operations comprising:

perform path segmentation on the tracking path;

determine a shape that bounds the Wi-Fi position system location estimates;

refining segmentation of the tracking path based on the reliability numbers assigned to the plurality of Wi-Fi position system location estimates; and

perform shape matching on the refined path segmentation.

20. The computer readable storage of claim 15, further comprising instructions, if executed by the processor, causes the processor to perform operations comprising:

provide a corrected path based on the tracking related parameter.