Method and electronic device for improving accuracy of measurement of motion sensor

• US 10,001,505 B2
• Filed: 03/07/2016
• Issued: 06/19/2018
• Est. Priority Date: 03/06/2015
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Babu, Swarna Ravindra, Rakesh, C, Dhineshkumar, C, Swaroop, Y Megha, Siddanahalli Ninge Gowda, Arun Kumar, Bhatt, Deepak
• Primary Examiner(s): McCall, Eric S
• Assistant Examiner(s): Keramet-Amircola, Mohammed E
• Application Number:
  US15/062,831
• Publication Number:
  US 20160258978A1
• Time in Patent Office: 834 Days
• Field of Search: 73 138
• CPC Class Codes: G01C 19/5776 Signal processing not specific to any of the devices covered by groups G01C19/5607 - G01C19/5719
• 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 of improving accuracy of measurements of at least one motion sensor included in an electronic device, including receiving a candidate measurement associated with the electronic device from the at least one motion sensor; detecting an electronic device state associated with the electronic device, the electronic device state including one from among a static state and a motion state; computing a compensation parameter based on the candidate measurement and the electronic device state; and correcting the candidate measurement based on the computed compensation parameter.

Claims

1. A method of improving accuracy of measurements of at least one motion sensor included in an electronic device, the method comprising:

receiving a candidate measurement associated with the electronic device from the at least one motion sensor;

detecting an electronic device state associated with the electronic device, wherein the electronic device state is one of a static state and a motion state;

computing a compensation parameter by estimating a bias based on the candidate measurement and the electronic device state; and

correcting the candidate measurement based on the computed compensation parameter,

wherein the computing the compensation parameter comprises;

estimating the bias when the electronic device state is detected as the static state, or computing orientation information from the candidate measurement received from the motion sensor when the electronic device state is detected as the motion state and estimating the bias based on the orientation information.

2. The method of claim 1, wherein the compensation parameter further includes at least one from among heuristic derived inferences, and machine learning derived inferences.

3. The method of claim 1, wherein the correcting the candidate measurement further comprises compensating the candidate measurement with the bias.

4. The method of claim 1, wherein the correcting the candidate measurement further comprises compensating the candidate measurement with the estimated bias.

5. The method of claim 1, wherein the computing the compensation parameter further comprises identifying an odd number of zero crossings of the candidate measurement, the zero crossings being generated when the electronic device state is detected as the motion state, and estimating the bias based on an average of the candidate measurement, and

wherein the correcting the candidate measurement further comprises compensating the candidate measurement with the estimated bias.

6. The method of claim 1, wherein the computing the compensation parameter further comprises estimating a delta change in an angle corresponding to an estimate of a heading of the electronic device due to a user motion when the electronic device state is detected as the motion state.

7. The method of claim 6, wherein, if the delta change is below a threshold value, the candidate measurement is regarded as an effect of the bias and the estimate of the heading is corrected by compensating the heading estimate with the delta change.

8. The method of claim 6, wherein if the delta change is greater than a threshold value and below a shaping angle, the correcting the candidate measurement further comprises compensating the candidate measurement with the shaping angle.

9. The method of claim 1, wherein the computing the compensation parameter further comprises:

clustering the candidate measurement into a cluster from among a plurality of clusters; and

tagging the cluster as corresponding to a turn movement or a non-turn movement based on information of the candidate measurement,

wherein the compensation parameter is used to correct the candidate measurement if the cluster is tagged as corresponding to the turn movement.

10. A non-transitory computer readable recording medium storing computer executable program codes, which when executed by a processor, cause the processor to perform the method of claim 1.

11. An electronic device for improving accuracy of measurements of at least one motion sensor, the electronic device comprising:

a sensor configured to sense a candidate measurement associated with the electronic device through the at least one motion sensor; and

a data processor configured to;

receive the candidate measurement associated with the electronic device from the at least one motion sensor;

detect an electronic device state associated with the electronic device, wherein the electronic device state is one of a static state and a motion state;

compute a compensation parameter based on the candidate measurement and the electronic device state; and

correct the candidate measurement based on the computed compensation parameter.

12. The electronic device of claim 11, wherein the compensation parameter further includes one from among heuristic based inferences, and machine learning based inferences.

13. The electronic device of claim 12, wherein the data processor is configured to:

identify an odd number of zero crossings of the candidate measurement, the zero crossings being generated when the electronic device state is detected as the motion state;

estimate the bias based on an average of the candidate measurement; and

correct the candidate measurement by compensating the candidate measurement with the estimated bias.

14. The electronic device of claim 12, wherein the data processor is configured to estimate a delta change in an angle corresponding to an estimate of a heading of the electronic device due to a human motion when the electronic device state is detected as the motion state.

15. The electronic device of claim 12, wherein the data processor is configured to:

cluster the candidate measurement into a cluster from among a plurality of clusters; and

tag the cluster as corresponding to a turn movement or a non-turn movement based on information of the candidate measurement,

wherein the compensation parameter is used to correct the candidate measurement if the cluster is tagged as corresponding to the turn movement.

16. A method for correcting a measurement made by a motion sensor included in an electronic device, the method comprising:

receiving a plurality of motion measurements associated with the electronic device from the at least one motion sensor, the plurality of motion measurements including a candidate motion measurement;

detecting a motion pattern associated with the plurality of motion measurements;

computing a compensation parameter by estimating a bias based on the detected motion pattern; and

correcting the candidate motion measurement based on the computed compensation parameter,

wherein the method further comprises estimating the bias when the electronic device state is detected as the static state, or computing orientation information from the candidate measurement received from the motion sensor when the electronic device state is detected as the motion state and estimating the bias based on the orientation information.

17. The method of claim 16, wherein the plurality of motion measurements are associated with a motion history of the electronic device, and wherein the candidate motion measurement is associated with a current motion of the electronic device.

18. The method of claim 17, wherein the motion pattern corresponds to at least one from among an orientation associated with the electronic device, a walking motion associated with a user of the electronic device, or an angle of a motion heading associated with the electronic device.