In-use automatic calibration methodology for sensors in mobile devices

• US 9,683,865 B2
• Filed: 10/12/2012
• Issued: 06/20/2017
• Est. Priority Date: 01/26/2012
• Status: Active Grant

• Current Assignee: Invensense Incorporated (TDK Corporation)
• Original Assignee: Invensense Incorporated (TDK Corporation)
• Inventors: Keal, William Kerry, Zheng, Yuan, Lin, Shang-Hung, Gu, Anjia, Lim, James
• Primary Examiner(s): Breene, John
• Assistant Examiner(s): AIELLO, JEFFREY P
• Application Number:
  US13/650,480
• Publication Number:
  US 20130197845A1
• Time in Patent Office: 1,712 Days
• Field of Search: 73 176, 73 177, 73 175, 702 85, 702141, 702145, 702150, 702161, 702153, 702104, 701472, 701500
• CPC Class Codes: G01C 25/005 initial alignment, calibration or starting-up of inertial devices
• CPC Class Codes: G01P 21/00 Testing or calibrating of apparatus or devices covered by the preceding groups

Abstract

A method, system and computer readable medium for calibrating an accelerometer in a portable device is disclosed. The method, system and computer readable medium comprises receiving data from the accelerometer, and providing accelerometer samples from the data based upon one or more selection rules that adaptively selects data that satisfy certain criteria. The method system and computer readable medium also includes fitting the accelerometer samples to a mathematical mode. The method system and computer readable medium further includes providing a bias of the accelerometer based upon a center of the mathematical model.

Claims

1. A method of calibrating an accelerometer in a portable device comprising:

receiving data from the accelerometer;

providing accelerometer samples from the data based upon one or more selection rules that adaptively selects data that satisfy certain criteria;

wherein the selection rules includes a rule wherein a variation of the linear acceleration is below a threshold to select a small set of accelerometer samples at a plurality of orientations;

fitting the small set of accelerometer samples to a mathematical model to facilitate learning a bias of the accelerometer; and

providing the bias based upon a center of the mathematical model;

wherein the bias is calculated automatically as a user uses the portable device.

2. The method of claim 1, further comprising receiving data from a gyroscope.

3. The method of claim 1, where the mathematical model is a sphere.

4. The method of claim 1, where the mathematical model is an ellipsoid.

5. The method of claim 4, where the stretch of each axis of the ellipsoid is equivalent of scaling of the corresponding axis.

6. The method of claim 1, wherein the selection rules select a subset of the data to provide the accelerometer samples.

7. The method of claim 2, wherein the selection rules include an in-motion selection rule wherein the derivative of acceleration is a function of the gyroscope and orientation of the device.

8. The method of claim 1, wherein the selection rules includes variation of the linear acceleration is below a threshold.

9. The method of claim 2, wherein the selection rules includes a rotation rate of the device.

10. The method of claim 9, the rotation rate is determined from the gyroscope or quaternion derivative.

11. The method of claim 2, where the gyroscope data is used to determine whether the device is substantially steady.

12. The method of claim 1, wherein the portable device is held substantially steady.

13. The method of claim 1, where the selection rules includes, utilizing a least square method to estimate a three axis bias and a radius of a sphere if three axes share the same radius.

14. The method of claim 1, further comprising storing information related to the accelerometer samples.

15. The method of claim 12, the information includes statistical features.

16. The method of claim 12, the information includes 2.sup.nd, 3.sup.rd and 4th order of the data.

17. The method of claim 1, further comprising erasing the stored information when the linear acceleration is above a threshold value and the portable device is substantially steady.

18. The method of claim 1, further comprising selecting an axis for providing the bias.

19. The method of claim 16, further the selecting an axis includes selecting a first axis when magnitude of data along the first axis is greater than magnitude of accelerometer data multiplied by a threshold, where in the magnitude of the accelerometer data square is sum of the square of the data along the first axis, second axis and the third axis.

20. The method of claim 17, selecting a second axis when the magnitude of the data along the first axis is lesser than the magnitude of the data vector multiplied by the threshold, and when the magnitude of data along the second axis is greater than the magnitude of the data vector multiplied by a threshold.

21. The method of claim 15, selecting a third axis when the magnitude of the data along the second axis is lesser than the magnitude of the data vector multiplied by a threshold, and when the magnitude of the data along the third axis is greater than the magnitude of the vector multiplied by a threshold.

22. The method of claim 1, wherein second data related to the second axis and a third data value related to third axis are small, bias of the first axis is set to the difference of 1 and the first data along the first axis.

23. The method of claim 1, where in selecting an axis includes sensing a rotation of the device above a third threshold angle.

24. A non-transitory computer program product stored on a computer readable medium, comprising:

computer readable program means for causing a computer to control an execution of an application to perform a method for calibrating an accelerometer in a portable device comprising;

receiving data from the accelerometer;

providing accelerometer samples from the data based upon one or more selection rules that adaptively selects data that satisfy certain criteria;

wherein the selection rules includes a rule wherein a variation of the linear acceleration is below a threshold to select a small set of accelerometer samples at a plurality of orientations;

fitting the small set of accelerometer samples to a mathematical model to facilitate learning a bias of the accelerometer; and

providing the bias of the accelerometer based samples upon a center of the mathematical model;

wherein the bias is calculated automatically as a user uses the portable device.