System and method for determining an attitude of a device undergoing dynamic acceleration using a Kalman filter

• US 8,515,707 B2
• Filed: 05/06/2009
• Issued: 08/20/2013
• Est. Priority Date: 01/07/2009
• Status: Expired due to Fees

• Current Assignee: Sensor Platforms, Incorporated (Knowles Corporation)
• Original Assignee: Sensor Platforms, Incorporated (Knowles Corporation)
• Inventors: Joseph, Benjamin E., Shaw, Kevin A., Chen, Ian
• Primary Examiner(s): Nghiem, Michael
• Assistant Examiner(s): Satanovsky, Alexander
• Application Number:
  US12/436,727
• Publication Number:
  US 20100174506A1
• Time in Patent Office: 1,567 Days
• Field of Search: 702/141, 702/150
• US Class Current: 702/141
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G06F 3/0346 with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06F 3/038 Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry

Abstract

A system, a computer readable storage medium including instructions, and a method for determining an attitude of a device undergoing dynamic acceleration. A difference between a first accelerometer measurement received from a first multi-dimensional accelerometer of the device and a second accelerometer measurement received from a second multi-dimensional accelerometer of the device is calculated. A Kalman gain is adjusted based on the difference, wherein the Kalman gain is used in a Kalman filter that determines the attitude of the device. An attitude of the device is determined using the Kalman filter based at least in part on the Kalman gain, the first accelerometer measurement, the second accelerometer measurement, and a magnetic field measurement received from a multi-dimensional magnetometer of the device.

Claims

1. A method for determining an attitude of a device undergoing dynamic acceleration, comprising:

at one or more systems having one or more processors and memory storing one or more programs that, when executed by the one or more processors, cause the one or more systems to perform the method;

calculating a difference between a first accelerometer measurement received from a first multi-dimensional accelerometer of the device and a second accelerometer measurement received from a second multi-dimensional accelerometer of the device;

adjusting a Kalman gain based on the difference, wherein;

the Kalman gain is used in a Kalman filter that determines the attitude of the device; and

when the difference is less than a specified threshold, adjusting the Kalman gain based on the difference includes decreasing covariance values associated with the first accelerometer measurement and the second accelerometer measurement in a measurement covariance matrix of the Kalman filter so that the first accelerometer measurement and the second accelerometer measurement are given more weight in the Kalman filter relative to a magnetic field measurement received from a multi-dimensional magnetometer of the device than when the difference is greater than the specified threshold; and

determining an attitude of the device using the Kalman filter based at least in part on the Kalman gain, the first accelerometer measurement, the second accelerometer measurement, and the magnetic field measurement.

2. The method of claim 1, wherein when the difference is greater than a specified threshold, adjusting the Kalman gain based on the difference includes increasing covariance values associated with the first accelerometer measurement and the second accelerometer measurement in a measurement covariance matrix of the Kalman filter so that the first accelerometer measurement and the second accelerometer measurement are given less weight in the Kalman filter relative to the magnetic field measurement than when the difference is less than the specified threshold.

3. The method of claim 1, wherein the first accelerometer measurement, the second accelerometer measurement and the magnetic field measurement are sensor measurements corresponding to a same update period for the Kalman filter.

4. The method of claim 1, wherein the one or more systems comprise the device undergoing dynamic acceleration.

5. The method of claim 1, wherein the one or more systems comprise a host system that is different from the device undergoing dynamic acceleration.

6. The method of claim 1, wherein a state vector of the Kalman filter includes state values representing:

the attitude of the device;

a rate at which the attitude of the device is rotating;

a radius of rotation between one of the first and the second the multi-dimensional accelerometers and a pivot point;

a first bias value of the difference in a first axis; and

a second bias value of the difference in a second axis.

7. The method of claim 6, wherein the attitude of the device is represented using a quaternion.

8. The method of claim 7, wherein the quaternion includes:

a unit vector representing a direction; and

a rotation angle about the unit vector.

9. A system for determining an attitude of a device undergoing dynamic acceleration, comprising:

one or more processors;

memory; and

one or more programs stored in the memory, the one or more programs comprising instructions to;

calculate a difference between a first accelerometer measurement received from a first multi-dimensional accelerometer of the device and a second accelerometer measurement received from a second multi-dimensional accelerometer of the device;

adjust a Kalman gain based on the difference, wherein;

the Kalman gain is used in a Kalman filter that determines the attitude of the device; and

when the difference is less than a specified threshold, the instructions to adjust the Kalman gain based on the difference include instructions to decrease covariance values associated with the first accelerometer measurement and the second accelerometer measurement of the Kalman filter so that the first accelerometer measurement and the second accelerometer measurement are given more weight in the Kalman filter relative to a magnetic field measurement received from a multi-dimensional magnetometer of the device than when the difference is greater than the specified threshold; and

determine an attitude of the device using the Kalman filter based at least in part on the Kalman gain, the first accelerometer measurement, the second accelerometer measurement, and the magnetic field measurement.

10. The system of claim 9, wherein when the difference is greater than a specified threshold, the instructions to adjust the Kalman gain based on the difference include instructions to increase covariance values associated with the first accelerometer measurement and the second accelerometer measurement in a measurement covariance matrix of the Kalman filter so that the first accelerometer measurement and the second accelerometer measurement are given less weight in the Kalman filter relative to the magnetic field measurement than when the difference is less than the specified threshold.

11. The system of claim 9, wherein the first accelerometer measurement, the second accelerometer measurement and the magnetic field measurement are sensor measurements corresponding to a same update period for the Kalman filter.

12. The system of claim 9, wherein a state vector of the Kalman filter includes state values representing:

the attitude of the device;

a rate at which the attitude of the device is rotating;

a radius of rotation between one of the first and the second the multi-dimensional accelerometers and a pivot point;

a first bias value of the difference in a first axis; and

a second bias value of the difference in a second axis.

13. The system of claim 12, wherein the attitude of the device is represented using a quaternion.

14. The system of claim 13, wherein the quaternion includes:

a unit vector representing a direction; and

a rotation angle about the unit vector.

15. A non-transitory computer readable storage medium storing one or more programs configured for execution by a processor, the one or more programs comprising instructions to:

calculate a difference between a first accelerometer measurement received from a first multi-dimensional accelerometer of a device and a second accelerometer measurement received from a second multi-dimensional accelerometer of the device;

adjust a Kalman gain based on the difference, wherein;

the Kalman gain is used in a Kalman filter that determines the attitude of the device; and

when the difference is less than a specified threshold, the instructions to adjust the Kalman gain based on the difference include instructions to decrease covariance values associated with the first accelerometer measurement and the second accelerometer measurement so that the first accelerometer measurement and the second accelerometer measurement are given more weight in the Kalman filter relative to a magnetic field measurement received from a multi-dimensional magnetometer of the device than when the difference is greater than the specified threshold; and

determine an attitude of the device using the Kalman filter based at least in part on the Kalman gain, the first accelerometer measurement, the second accelerometer measurement, and the magnetic field measurement.

16. The computer readable storage medium of claim 15, wherein the first accelerometer measurement, the second accelerometer measurement and the magnetic field measurement are sensor measurements corresponding to a same update period for the Kalman filter.

17. The computer readable storage medium of claim 15, wherein when the difference is greater than a specified threshold, the instructions to adjust the Kalman gain based on the difference include instructions to increase covariance values associated with the first accelerometer measurement and the second accelerometer measurement in a measurement covariance matrix of the Kalman filter so that the first accelerometer measurement and the second accelerometer measurement are given less weight in the Kalman filter relative to the magnetic field measurement than when the difference is less than the specified threshold.

18. The computer readable storage medium of claim 15, wherein a state vector of the Kalman filter includes state values representing:

the attitude of the device;

a rate at which the attitude of the device is rotating;

a radius of rotation between one of the first and the second the multi-dimensional accelerometers and a pivot point;

a first bias value of the difference in a first axis; and

a second bias value of the difference in a second axis.

19. The computer readable storage medium of claim 18, wherein the attitude of the device is represented using a quaternion.

20. The computer readable storage medium of claim 19, wherein the quaternion includes:

a unit vector representing a direction; and

a rotation angle about the unit vector.