Navigation system, method and software for foot travel

• US 6,522,266 B1
• Filed: 05/17/2000
• Issued: 02/18/2003
• Est. Priority Date: 05/17/2000
• Status: Expired due to Term

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell Incorporated (Honeywell International Inc.)
• Inventors: Soehren, Wayne A., Keyes, Charles L., Bye, Charles T.
• Primary Examiner(s): TWEEL JR, JOHN ALEXANDER
• Application Number:
  US09/572,238
• Time in Patent Office: 1,007 Days
• Field of Search: 340/988, 731/78.R, 377/24.2, 377/39, 482/3, 482/8, 482/74, 600/595, 702/97, 702/160
• US Class Current: 340/988
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G01C 17/00 Compasses; Devices for ascertaining true or magnetic north for navigation or surveying purposes using gyroscopic effect G01C19/00
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
• CPC Class Codes: G01S 19/41 Differential correction, e.g. DGPS [differential GPS]
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled
• CPC Class Codes: G01S 5/017 Detecting state or type of motion
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A navigation system for mounting on a human. The navigation system includes one or more motion sensors for sensing motion of the human and outputting one or more corresponding motion signals. An inertial processing unit coupled to one or more of motion sensors determines a first position estimate based on one or more of the corresponding signals from the motion sensors. A distance traveled is determined by a motion classifier coupled to one or more of the motion sensors, where the distance estimate is based on one or more of the corresponding motion signals processed in one or more motion models. A Kalman filter is also integrated into the system, where the Kalman filter receives the first position estimate and the distance estimate and provides corrective feedback signals to the inertial processor for the first position estimate. In an additional embodiment, input from a position indicator, such as a GPS, provides a third position estimate, and where the Kalman filter provides corrections to the first position estimate, the distance estimate and parameters of the motion model being used.

Claims

1. A navigation system for mounting on a human, the navigation system comprising:

one or more motion sensors for sensing motion of the human and outputting one or more corresponding motion signals;

first means coupled to one or more of the motion sensors to determine a first position estimate based on one or more of the corresponding signals;

means for determining a magnetic heading and an inertial heading;

a Kalman filter to provide correction values to the first position estimate using past and present values of the motion signals and to produce a blended heading from the magnetic heading and the inertial heading; and

second means coupled to one or more of the motion sensors to determine a distance estimate based on one or more of the corresponding signals.

2. The system of claim 1, wherein the first and second means include at least one common motion sensor.

3. The system of claim 1, wherein the second means includes an electronic compass and the first means does not.

4. The system of claim 1, wherein the first means includes an inertial processor and the second means does not.

5. The system of claim 1, wherein the first and second means include a common processor.

6. The system of claim 1, wherein the Kalman filter respectively outputs first correction signals to the first means.

7. The system of claim 6, including an output terminal, where the output terminal displays the first position estimates in a human-perceptible form.

8. The system of claim 6, including:

means to determine a second position estimate; and

means for the Kalman filter to provide corrections to the first position estimate and the distance estimate using the second position estimate.

9. The system of claim 8, including means to determine the distance estimate from a motion model.

10. The system of claim 9, including means for identifying errors in the distance estimate;

and

means for modifying parameters of the motion model based on the errors in the distance estimate.

11. The system of claim 1, further including means, including one or more straps, for mounting the navigation system to a portion of the human.

12. A navigation system for mounting on a human, the navigation system comprising:

one or more motion sensors for sensing motion of the human and outputting one or more corresponding motion signals;

an inertial processing unit coupled to one or more of motion sensors to determine a first position estimate and inertial heading based on one or more of the corresponding signals;

a motion classifier coupled to one or more of the motion sensors to determine a distance estimate based on one or more of the corresponding motion signals; and

a Kalman filter which receives the first position estimate and the distance estimate and provides corrective feedback signals to the inertial processor for the first position estimate, wherein the Kalman filter determines the corrective feedback signals based on the first position estimate and the distance estimate and past and present values of the motion signals, and wherein the Kalman filter produces a blended heading from a magnetic heading and the inertial heading.

13. The system of claim 12, wherein the motion classifier includes magnetic sensors for determining a motion direction and uses the motion direction to determine the distance estimate.

14. The system of claim 13, where the motion classifier includes a step-distance model and uses the step-distance model to determine the distance estimate.

15. The system of claim 14, where the motion classifier uses the motion sensor to determine the frequency of steps to determine the distance estimate.

16. The system of claim 12, wherein the motion classifier classifies a user'"'"'s motion as straight, turning, or unknown.

17. The system of claim 12, including a position indicator which determines a third position estimate, and where the Kalman filter provides corrections to the first position estimate and the distance estimate using the third position estimate.

18. The system of claim 17, where motion classifier uses a motion model to determine the distance estimate, and where the Kalman filter identifies errors in the distance estimate and modifies parameters of the motion model based on the errors in the distance estimate.

19. The system of claim 18, where the modified parameters are specific to one or more humans.

20. The system of claim 17, where the position indicator is a global positioning receiver/processor.

21. The system of claim 17, including an output terminal, where the output terminal displays the first position estimate in a human-perceptible form.

22. The system of claim 12, including one or more straps to mount the navigation system to a portion of the human.

23. A method of estimating foot-travel position, comprising:

providing one or more motion signals;

determining a first position estimate from the one or more motion signals;

determining a distance estimate from the one or more motion signals;

correcting the first position estimate, wherein correcting the first position estimate includes using a Kalman filter to provide corrections to the first position estimate based on past and present values of the motion signals; and

blending a magnetic heading and an inertial heading to produce a blended heading using the Kalman filter.

24. The method of claim 23, where correcting the first position estimate includes using past and present values of the motion signals.

25. The method of claim 23, including displaying the first position estimate in a human-perceptible form.

26. The method of claim 23, where correcting the first position estimate includes determining a second position estimate based on past and present motion signals.

27. The method of claim 23, including determining a third position estimate from a position indicator;

and

determining a difference between the distance estimate and the third position estimate, where the Kalman filter uses the difference in providing corrections to the first position estimate.

28. The method of claim 27, where determining the distance estimate from the one or more motion signals includes using a motion model.

29. The method of claim 28, including determining a difference between the distance estimate and the third position estimate;

identifying errors in the distance estimate; and

modifying parameters of the motion model based on the errors in the distance estimate.