Motion direction determination and application

• US 9,983,224 B2
• Filed: 05/02/2014
• Issued: 05/29/2018
• Est. Priority Date: 05/02/2014
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Pakzad, Payam, Kulik, Victor
• Primary Examiner(s): Lee, Paul D
• Assistant Examiner(s): Crohn, Mark
• Application Number:
  US14/268,962
• Publication Number:
  US 20150316578A1
• Time in Patent Office: 1,488 Days
• CPC Class Codes: G01B 7/00 Measuring arrangements characterised by the use of electric or magnetic techniques
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled
• CPC Class Codes: G01S 5/0278 involving statistical or probabilistic considerations G01S5/0252, G01S5/0294 take precedence
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering

Abstract

This disclosure provides devices, computer programs and methods for determining a motion direction. In one aspect, a mobile device includes sensors for measuring acceleration data. The mobile device also includes a processor and a memory that implement a motion direction estimation module configured to determine a primary axis of motion. The motion direction estimation module also determines a motion direction along the primary axis. The determination includes fitting the acceleration data, or data derived therefrom, to a bimodal distribution. A first peak of the bimodal distribution corresponds to a first motion direction along the primary axis, and a second peak corresponds to a second motion direction opposite the first. The motion direction estimation module is configured to estimate the motion direction based on the bimodal distribution. In some implementations, the motion direction estimation module selects the motion direction corresponding to the higher of the peaks as the estimated motion direction.

Claims

1. A method comprising:

obtaining acceleration data for a mobile device in each of one or more directions;

determining a primary axis of motion of the mobile device based at least in part on the acceleration data;

determining an estimated motion direction of the mobile device along the primary axis of motion, the determining including;

fitting the acceleration data, or data derived therefrom, to a bimodal distribution, wherein a first peak of the bimodal distribution corresponds to a first motion direction along the primary axis of motion, and wherein a second peak of the bimodal distribution corresponds to a second motion direction along the primary axis of motion opposite the first motion direction; and

determining the estimated motion direction of the mobile device relative to a coordinate system based at least in part on the bimodal distribution;

determining a reliability metric for the estimated motion direction; and

controlling a network interface of the mobile device such that the network interface is turned off or otherwise disabled if the reliability metric is above a threshold value, the network interface being configured to communicate with a Global Positioning System, Satellite Navigation System, or other positioning or navigation system.

2. The method of claim 1, wherein determining the motion direction of the mobile device relative to the coordinate system based at least in part on the bimodal distribution includes selecting the one of the first and second motion directions corresponding to the higher of the first and second peaks as the estimated motion direction of the mobile device.

3. The method of claim 1, further including comparing a first height of the first peak with a second height of the second peak and determining a reliability metric for the estimated motion direction based on a ratio of the first and second heights.

4. The method of claim 1, further including analyzing a width of at least the higher of the first and second peaks and determining a reliability metric for the estimated motion direction based on the width.

5. The method of claim 1, further including identifying an orientation of the mobile device relative to the coordinate system based on the acceleration data or other orientation data, wherein estimating the motion direction of the mobile device relative to the coordinate system also is based at least in part on the orientation.

6. The method of claim 5, wherein the orientation data includes one or both of gyroscopic data and magnetometer data.

7. The method of claim 1, further including tracking a number of steps taken by a person carrying the mobile device or to which the mobile device is attached.

8. The method of claim 1, wherein obtaining acceleration data for the mobile device includes:

measuring a first linear acceleration of the mobile device along a first directional axis in a mobile device coordinate system;

measuring a second linear acceleration of the mobile device along a second directional axis in the mobile device coordinate system; and

measuring a third linear acceleration of the mobile device along a third directional axis in the mobile device coordinate system.

9. The method of claim 8, further including transforming the first, second and third linear accelerations in the mobile device coordinate system into first, second and third linear accelerations in a global coordinate system, wherein:

the global coordinate system is the coordinate system;

the first linear acceleration in the global coordinate system is a first horizontal acceleration;

the second linear acceleration in the global coordinate system is a second horizontal acceleration; and

the third linear acceleration in the global coordinate system is a vertical acceleration.

10. The method of claim 9, wherein determining a primary axis of motion of the mobile device based at least in part on the acceleration data includes performing an eigendecomposition on at least the first and second horizontal accelerations to identify at least a first eigenvalue and a second eigenvalue, the first eigenvalue corresponding to a first horizontal eigenvector and the second eigenvalue corresponding to a second horizontal eigenvector.

11. The method of claim 10, wherein the first peak of the bimodal distribution corresponds to positive values of the first eigenvalue and the second peak of the bimodal distribution corresponds to negative values of the first eigenvalue.

12. A mobile device comprising:

one or more sensors configured to measure acceleration data for the mobile device in each of one or more directions;

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, implement a motion direction estimation module configured to;

determine a primary axis of motion of the mobile device based at least in part on the acceleration data;

determine an estimated motion direction of the mobile device along the primary axis of motion, the determination including;

fitting the acceleration data, or data derived therefrom, to a bimodal distribution, wherein a first peak of the bimodal distribution corresponds to a first motion direction along the primary axis of motion, and wherein a second peak of the bimodal distribution corresponds to a second motion direction along the primary axis of motion opposite the first motion direction; and

determining the estimated motion direction of the mobile device relative to a coordinate system based at least in part on the bimodal distribution;

determine a reliability metric for the estimated motion direction; and

control a network interface of the mobile device such that the network interface is turned off or otherwise disabled if the reliability metric is above a threshold value, the network interface being configured to communicate with a Global Positioning System, Satellite Navigation System, or other positioning or navigation system.

13. The mobile device of claim 12, wherein to determine the motion direction of the mobile device relative to the coordinate system based at least in part on the bimodal distribution, the motion direction estimation module is configured to select the one of the first and second motion directions corresponding to the higher of the first and second peaks as the estimated motion direction of the mobile device.

14. The mobile device of claim 12, wherein the memory further stores instructions that, when executed by the one or more processors, implement a reliability metric computation module configured to compare a first height of the first peak with a second height of the second peak and to determine a reliability metric for the estimated motion direction based on a ratio of the first and second heights.

15. The mobile device of claim 12, wherein the memory further stores instructions that, when executed by the one or more processors, implement a reliability metric computation module configured to analyze a width of at least the higher of the first and second peaks and to determine a reliability metric for the estimated motion direction based on the width.

16. The mobile device of claim 12, wherein the memory further stores instructions that, when executed by the one or more processors, implement an orientation determination module configured to identify an orientation of the mobile device relative to the coordinate system based on the acceleration data or other orientation data, wherein the motion direction estimation module also is configured to estimate the motion direction of the mobile device based at least in part on the orientation.

17. The mobile device of claim 16, wherein the one or more sensors include one or more gyroscopes or one or more magnetometers, and wherein the orientation data includes one or both of gyroscopic data and magnetometer data.

18. The mobile device of claim 12, wherein the memory further stores instructions that, when executed by the one or more processors, implement a step detection module configured to track a number of steps taken by a person carrying the mobile device or to which the mobile device is attached.

19. The mobile device of claim 12, wherein:

the one or more sensors include;

a first linear accelerometer configured to measure a first linear acceleration of the mobile device along a first directional axis in a mobile device coordinate system;

a second linear accelerometer configured to measure a second linear acceleration of the mobile device along a second directional axis in the mobile device coordinate system; and

a third linear accelerometer configured to measure a third linear acceleration of the mobile device along a third directional axis in the mobile device coordinate system; and

the motion direction estimation module is further configured to transform the first, second and third linear accelerations in the mobile device coordinate system into first, second and third linear accelerations in a global coordinate system, wherein;

the global coordinate system is the coordinate system;

the first linear acceleration in the global coordinate system is a first horizontal acceleration;

the second linear acceleration in the global coordinate system is a second horizontal acceleration; and

the third linear acceleration in the global coordinate system is a vertical acceleration.

20. The mobile device of claim 19, wherein to estimate the primary axis of motion of the mobile device relative to the coordinate system, the motion direction estimation module is configured to perform an eigendecomposition on at least the first and second horizontal accelerations to identify at least a first eigenvalue and a second eigenvalue, the first eigenvalue corresponding to a first horizontal eigenvector and the second eigenvalue corresponding to a second horizontal eigenvector.

21. The mobile device of claim 20, wherein the first peak of the bimodal distribution corresponds to positive values of the first eigenvalue and the second peak of the bimodal distribution corresponds to negative values of the first eigenvalue.

22. One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, are configured to:

receive acceleration data for a mobile device in each of one or more directions;

determine a primary axis of motion of the mobile device based at least in part on the acceleration data;

determine an estimated motion direction of the mobile device along the primary axis of motion, the determination including;

fitting the acceleration data, or data derived therefrom, to a bimodal distribution, wherein a first peak of the bimodal distribution corresponds to a first motion direction along the primary axis of motion, and wherein a second peak of the bimodal distribution corresponds to a second motion direction along the primary axis of motion opposite the first motion direction; and

determining the estimated motion direction of the mobile device relative to a coordinate system based at least in part on the bimodal distribution;

determine a reliability metric for the estimated motion direction; and

control a network interface of the mobile device such that the network interface is turned off or otherwise disabled if the reliability metric is above a threshold value, the network interface being configured to communicate with a Global Positioning System, Satellite Navigation System, or other positioning or navigation system.

23. The one or more non-transitory media of claim 22, wherein the instructions for determining the motion direction include instructions for selecting the one of the first and second motion directions corresponding to the higher of the first and second peaks as the estimated motion direction of the mobile device.

24. The one or more non-transitory media of claim 22, further including instructions for comparing a first height of the first peak with a second height of the second peak and for determining a reliability metric for the estimated motion direction based on a ratio of the first and second heights.

25. The one or more non-transitory media of claim 22, further including instructions for analyzing a width of at least the higher of the first and second peaks and for determining a reliability metric for the estimated motion direction based on the width.

26. The one or more non-transitory media of claim 22, further including instructions for identifying an orientation of the mobile device relative to the coordinate system based on the acceleration data or other orientation data, wherein the estimated motion direction of the mobile device is based at least in part on the orientation.

27. The one or more non-transitory media of claim 22, further including instructions for tracking a number of steps taken by a person carrying the mobile device or to which the mobile device is attached.

28. The one or more non-transitory media of claim 22, wherein the instructions for estimating the primary axis of motion of the mobile device include instructions for performing an eigendecomposition on the acceleration data to identify at least a first eigenvalue and a second eigenvalue corresponding to a first horizontal eigenvector and a second horizontal eigenvector.

29. The one or more non-transitory media of claim 28, wherein the first peak of the bimodal distribution corresponds to positive values of the first eigenvalue and the second peak of the bimodal distribution corresponds to negative values of the first eigenvalue.