Comprehensive sensor fusion algorithm

• US 9,864,729 B1
• Filed: 12/21/2012
• Issued: 01/09/2018
• Est. Priority Date: 12/21/2012
• Status: Active Grant

• Current Assignee: Hanking Electronics Hongkong Company Limited
• Original Assignee: Hanking Electronics, Ltd.
• Inventors: Sala, Leonardo, Cazzaniga, Gabriele, Sabatelli, Simone
• Primary Examiner(s): Nghiem, Michael
• Application Number:
  US13/724,840
• Time in Patent Office: 1,845 Days
• Field of Search: 702141, 702150
• CPC Class Codes: G06F 17/15 Correlation function computation including computation of convolution operations arithmetic circuits for sum of products per se, e.g. multiply-accumulators G06F7/5443; digital filters, e.g. FIR, IIR, adaptive filters H03H17/00
• CPC Class Codes: G06F 18/251 of input or preprocessed data
• CPC Class Codes: G06F 2218/10 by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

Abstract

The present invention relates to a signal processor, and more particularly, to systems, devices and methods of using a comprehensive sensor fusion algorithm to integrate sensor data collected by accelerometers, gyroscopes and magnetometers. The signal processor dynamically applies a Complementary Filter to merge a rotation based gyro output and a FQA output that is obtained by combining acceleration rates and magnetic field magnitudes. Therefore, motion information is derived to generate a motion control signal. Such a comprehensive sensor fusion algorithm significantly reduces the complexity of computation, and the power and area overhead is controlled. As a result, the signal processor may be implemented based on local computation capability of a sensor system, and its integration within such a sensor system is made possible without relying on an external microprocessor.

Claims

1. A signal processor based on a comprehensive sensor fusion algorithm, comprising:

a Factored Quaternion Algorithm (FQA) processor, coupled to at least one accelerometer and at least one magnetometer, the FQA processor combining one or more acceleration rates and one or more magnetic field magnitudes to generate an FQA output;

a gyro-processor, coupled to at least one gyroscope, the gyro-processor generating a gyro output based on one or more rotation rates; and

a complementary filter, coupled to the FQA processor and the gyro-processor, the complementary filter combining the FQA and gyro outputs and generating a motion control signal, the complementary filter having a characteristic frequency and different scale factors that depend on the characteristic frequency and apply different weights based on the different scale factors to the FQA output and the gyro output, wherein the characteristic frequency and the scale factors of the complementary filter being dynamically adjusted based on the magnitude of at least one of the plurality of acceleration rates.

2. The signal processor according to claim 1, wherein the one or more acceleration rates, the one or more rotation rates and the one or more magnetic field magnitudes are associated with a plurality of distinct sensing axes, and orientations of the sensing axes are determined with respect to a fixed reference frame in order to generate the motion control signal.

3. The signal processor according to claim 2, wherein the fixed reference frame is an earth coordinate system based on three orthogonal axes that are aligned to a longitude line, a latitude line and a direction of a gravity gravitational acceleration.

4. The signal processor according to claim 1, wherein the FQA output and the gyro output are associated with a first quaternion and a second quaternion, respectively.

5. The signal processor according to claim 1, wherein lower and higher distinct frequency domains on two sides of the characteristic frequency are identified for the complementary filter, the complementary filter uses a larger scale factor for the FQA output than for the gyro output in the lower frequency domain, and the complementary filter uses a larger scale factor for the gyro output than for the FQA in the higher frequency domain.

6. The signal processor according to claim 5, further comprising:

an adaptive pole controller, coupled to the at least one accelerometer, the adaptive pole controller generating a pole control signal to control the characteristic frequency of the complementary filter based on the magnitude of at least one of the one or more acceleration rates.

7. The signal processor according to claim 5, wherein the characteristic frequency is adaptively controlled to a lower frequency when a magnitude of at least one of the one or more acceleration rates increases, and, conversely, to a higher frequency when the magnitude of the at least one of the one or more acceleration rates drops.

8. The signal processor according to claim 1, further comprising a gyro controller that generates a gyro control signal to disable the gyro-processor in response to detecting at least one of an acceleration rate and a certain level of magnetic interference reaching a respective threshold value.

9. A method for integrating sensor data, comprising the steps of:

receiving at least one acceleration rate, at least one magnetic field magnitude and at least one rotation rate;

using the at least one acceleration rate and magnetic field magnitude to generate a first quaternion based on a Factored Quaternion Algorithm (FQA);

generating a gyro output that is based on the at least one rotation rate to generate a second quaternion; and

processing the first and second quaternions and the gyro output by a complementary filter to generate a motion control signal, the complementary filter compensating a drift of the at least one rotation rate, the complementary filter having a characteristic frequency and different scale factors that depend on the characteristic frequency and apply different weights based on the different scale factors to the FQA output and the gyro output, wherein the characteristic frequency and the scale factors of the complementary filter being dynamically adjusted based on the magnitude of at least one of the plurality of acceleration rates.

10. The method according to claim 9, wherein the at least one acceleration rate, the at least one magnetic field magnitude, and the at least one rotation rate are associated with a plurality of distinct sensing axes whose orientations are determined with respect to a fixed reference frame.

11. The method according to claim 10, wherein the fixed reference frame is an earth coordinate system based on three orthogonal axes that are aligned to a longitude line, a latitude line and a direction of a gravitational acceleration.

12. The method according to claim 9, wherein the first quaternion comprises a vector.

13. The method according to claim 9, wherein the complementary filter has lower and higher distinct frequency domains on two sides of the characteristic frequency, the complementary filter uses a larger scale factor for the FQA output than for the gyro output in the lower frequency domain, and the complementary filter uses a larger scale factor for the gyro output than for the FQA in the higher frequency domain.

14. The method according to claim 13, wherein the characteristic frequency is adaptively controlled to a lower frequency when a magnitude of at least one of the at least one acceleration rate increases, and conversely, to a higher frequency when the magnitude of the at least one of the at least one acceleration rate drops.

15. The method according to claim 9, wherein the step of generating a gyro output further comprising:

estimating motion in a low frequency domain; and

enabling compensation for a corresponding bias in the gyro output.