Methods for improved heading estimation

• US 10,393,543 B2
• Filed: 07/13/2017
• Issued: 08/27/2019
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Funk, Benjamin E., Hakim, Dan, Karvounis, John, Young, Travis, Teolis, Carole
• Primary Examiner(s): Le, John H
• Application Number:
  US15/649,571
• Publication Number:
  US 20170307404A1
• Time in Patent Office: 775 Days
• Field of Search: 702 92, 702 93, 702104, 702141, 33356, 34099519, 701446, 701495, 701500, 701510
• CPC Class Codes: G01C 17/38 Testing, calibrating, or compensating of compasses
• CPC Class Codes: G01C 25/00 Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass testing, calibrating or compensating compasses G01C17/38

Abstract

Methods for calibrating a body-worn magnetic sensor by spinning the magnetic sensor 360 degrees to capture magnetic data; if the spin failed to produce a circle contained in an x-y plane fit a sphere to the captured data; determining offsets based on the center of the sphere; and removing the offsets that are in the z-direction. Computing a magnetic heading reliability of a magnetic sensor by determining an orientation of the sensor at one location; transforming the orientation between two reference frames; measuring a first vector associated with the magnetic field of Earth at the location; processing the first vector to generate a virtual vector when a second location is detected; measuring a second vector associated with the magnetic field of Earth at the second location; and calculating the magnetic heading reliability at the second location based on a comparison of the virtual vector and the second vector.

Claims

1. A method for obtaining a global rotation estimation, comprising:

determining a path of a magnetic sensor and a gyro sensor in a device in motion in an environment based on magnetic data received from the magnetic sensor and gyro data received from the gyro sensor, the path comprising a plurality of path points;

segmenting the path such that path points are separated into a plurality of spatial grids;

determining magnetic headings from the magnetic data and gyro headings from the gyro data for the path points in each spatial grid among the plurality of spatial grids;

for each spatial grid, computing a grid value based on a function of the magnetic headings and the gyro headings at path points within each spatial grid;

determining an average of the grid values across the plurality of spatial grids; and

setting the global rotation estimation as a rotation value that minimizes the average of the grid values.

2. The method of claim 1, wherein there are two or more path points in a spatial grid, and wherein the grid value is a weighted average of the magnetic headings and the gyro headings at the two or more path points.

3. The method of claim 1, further comprising applying an error measure to the average of the grid values such that the global rotation estimation accounts for the error measure.

4. The method of claim 3, wherein the error measure comprises a standard deviation of the grid values of the plurality of spatial grids.

5. A computer-implemented method for spatially weighting a path constraint, comprising:

receiving sensor data from a tracked computing device, the sensor data including magnetic data from a magnetic sensor and gyro data from a gyro sensor;

determining a magnetic heading based on the magnetic data and a gyro heading based on the gyro data;

determining a path of the tracked computing device, the path comprising a plurality of path points based on the magnetic heading and the gyro heading;

segmenting the path such that path points are separated into a plurality of spatial grids;

for each spatial grid among the plurality of spatial grids, computing a grid value based on a function of the magnetic headings and the gyro headings at path points within each spatial grid;

determining an average grid value across the plurality of spatial grids; and

setting the path constraint as a constraint value that minimizes the average grid value.

6. The method of claim 5, wherein the path constraint is a rotation, a path scale, or a drift.

7. The method of claim 5, wherein the grid value is a weighted average of a difference between the magnetic heading and the gyro heading at the path points within each spatial grid.

8. The method of claim 5, further comprising applying an error measure to the average grid value to decrease error in the path constraint.

9. The method of claim 8, wherein the error measure comprises a standard deviation of the grid values of the plurality of spatial grids.

10. A computer readable storage medium comprising instructions that, when executed on a computing system of a tracked device having a magnetic sensor for a compass and a gyro sensor, cause the computing system to:

receive sensor data comprising magnetic data from the magnetic sensor and gyro data from the gyro sensor;

determine a magnetic heading based on the compass data and a gyro heading based on the gyro data;

determine a path of the tracked computing device, the path comprising a plurality of path points based on the magnetic heading and the gyro heading;

segment the path such that path points are separated into a plurality of spatial grids;

for each spatial grid among the plurality of spatial grids, compute a spatial grid heading based on a function of the magnetic headings and the gyro headings at path points within each spatial grid;

determine an average grid value across the plurality of spatial grids; and

set a path constraint as a constraint value that minimizes the average grid value.

11. The computer readable storage medium of claim 10, wherein the path constraint is a rotation, a path scale, or a drift.

12. The computer readable storage medium of claim 10, wherein the grid value is a weighted average of a difference between the magnetic heading and the gyro heading at the path points within each spatial grid.

13. The computer readable storage medium of claim 10, wherein the instructions, when executed on the processor, further cause the computer system to at least apply an error measure to the average grid value to decrease error in the path constraint.

14. The computer readable storage medium of claim 13, wherein the error measure comprises a standard deviation of the grid values of the plurality of spatial grids.

15. A computing system comprising:

a processor;

a memory communicatively coupled to the processor, the memory bearing instructions that, when executed on the processor, cause the computing system to;

receive sensor data from a tracked computing device, the sensor data including magnetic data from a magnetic sensor and gyro data from a gyro sensor;

determine a magnetic heading based on the magnetic data and a gyro heading based on the gyro data;

determine a path of the tracked computing device, the path comprising a plurality of path points based on the magnetic heading and the gyro heading;

segment the path such that path points are separated into a plurality of spatial grids;

for each spatial grid among the plurality of spatial grids, compute a grid value based on a function of the magnetic headings and the gyro headings at path points within each spatial grid;

determine an average grid value across the plurality of spatial grids; and

set a path constraint as a constraint value that minimizes the average grid value.

16. The system of claim 15, wherein the grid value is a weighted average of a difference between the magnetic heading and gyro heading at path points within the spatial grid.

17. The system of claim 15, wherein the instructions, when executed on the processor, further cause the computing system to at least apply an error measure to the average grid value to decrease error in the path constraint.

18. The system of claim 17, wherein the error measure comprises a standard deviation of the grid values of the plurality of spatial grids.