METHOD TO REDUCE DATA RATES AND POWER CONSUMPTION USING DEVICE BASED ATTITUDE GENERATION

• US 20140278215A1
• Filed: 08/12/2013
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Invensense Incorporated (TDK Corporation)
• Original Assignee: Invensense Incorporated (TDK Corporation)
• Inventors: Keal, William Kerry, Karahan, Sinan, Lim, James
• Granted Patent: US 10,247,748 B2
• Time in Patent Office: Days
• US Class Current: 702/150
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems
• CPC Class Codes: G01P 1/00 Details of instruments

Abstract

A method includes generating motion data by receiving a gyroscope data from a gyroscope sensor, performing integration using the gyroscope data and generating an integrated gyroscope data using a first processor. The method further includes receiving a data from one or more sensors, other than the gyroscope sensor, and performing sensor fusion using the integrated gyroscope data and the data to generate motion data using a second processor.

Claims

1. A method of generating motion data comprising;

receiving a gyroscope data from a gyroscope sensor;

performing integration using the gyroscope data and generating an integrated gyroscope data using a first processor;

receiving a data from one or more sensors, other than the gyroscope sensor; and

performing sensor fusion using the integrated gyroscope data and the data to generate motion data using at least one second processor.

2. The method of claim 1, wherein the gyroscope data includes one or more gyroscope data over a period of time.

3. The method of claim 1, wherein the data includes one or more data over a period of time.

4. The method of claim 1, wherein the one or more sensors include an accelerometer.

5. The method of claim 1, wherein the one or more sensors include a magnetometer.

6. The method of claim 1, wherein the one or more sensors include a pressure sensor, microphone, proximity sensor, or a light sensor.

7. The method of claim 1, wherein the gyroscope data is at a first data rate, the integrated gyroscope data is at a second data rate and the first data rate is higher than the second data rate.

8. The method of claim 1, further including performing bias removal prior to the performing integration step.

9. The method of claim 1, further including performing bias removal after the performing integration step.

10. The method of claim 1, further including performing bias removal and wherein the sensor fusion has an output and the performing bias removal step uses a current integrated gyroscope data and a previous integrated gyroscope data and a current sensor fusion output and a previous sensor fusion output.

11. The method of claim 1, wherein the gyroscope sensor is on a first device, the first processor is on a second device and the at least one second processor on a third device.

12. The method of claim 1, wherein the first processor and the gyroscope sensor are on a first device.

13. The method of claim 1, wherein the gyroscope sensor, the first processor, and the at least one second processor are on a first device.

14. The method of claim 1, wherein the gyroscope data is set to zero if the absolute value of the gyroscope data is less than a threshold.

15. The method of claim 1, wherein the integrated gyroscope data is a form of a quaternion.

16. The method of claim 15, wherein the quaternion is the normalized.

17. The method of claim 1, wherein at least a portion of the integrated gyroscope data is compressed.

18. The method of claim 1, wherein the performing integration step is performed starting from an initial data.

19. The method of claim 1, wherein the performing integration step has an integration time period associated with it and the integration time period is the same as the integrated gyroscope data rate.

20. The method of claim 1, wherein the performing integration step includes generating the integrated gyroscope data from two consecutive gyroscope data and a previous integrated gyroscope data.

21. The method of claim 1, further comprises:

receiving at least two consecutive gyroscope data from the gyroscope sensor;

averaging the at least two consecutive gyroscope data to generate an average data;

calculating a cross product of the at least two consecutive gyroscope data to generate a cross product data; and

the performing integration step further includes performing integration over a time interval using the average data and the cross product data.

22. The method of claim 1, further comprising performing a derivation of the integrated data by the at least one second processor to generate equivalent gyroscope data, wherein a gyroscope bias is computed using the equivalent gyroscope data.

23. The method of generating motion data,

receiving at least two consecutive gyroscope data from a gyroscope sensor;

averaging the at least two consecutive gyroscope data to generate average data;

calculating a cross product of the at least two consecutive gyroscope data to generate a cross product data; and

performing integration over a time interval using the average data and the cross product data.

24. The method of claim 23, wherein the performing integration comprises cosine and sine of the gyroscope data.

25. An apparatus for generating motion data comprising;

a gyroscope sensor providing a gyroscope data, the gyroscope data having associated therewith a first data rate;

one or more sensors operative to generate a data;

an integrator responsive to the gyroscope data and operative to generate an integrated gyroscope data having associated therewith a second data rate; and

a sensor fusion responsive to the integrated gyroscope data and the data and operative to generate motion data.

26. The apparatus of claim 25, wherein a first processor comprises the integrator and a second processor comprises the sensor fusion.