Determining and Correcting Error of Positional Vector-Valued Sensors Using a Fixed Angle Calibration Process

• US 20130338955A1
• Filed: 06/25/2013
• Published: 12/19/2013
• Est. Priority Date: 06/14/2012
• Status: Active Grant

• Current Assignee: Yost Labs, Inc.
• Original Assignee: YEI Corporation
• Inventors: Landers, Stephen P., Yost, Paul
• Granted Patent: US 9,255,799 B2
• Time in Patent Office: Days
• US Class Current: 702/92
• CPC Class Codes: G01C 17/38 Testing, calibrating, or compensating of compasses
• CPC Class Codes: G01C 25/005 initial alignment, calibration or starting-up of inertial devices
• CPC Class Codes: G01D 18/002 Automatic recalibration G01D18/008 takes precedence
• CPC Class Codes: G01D 18/008 with calibration coefficients stored in memory
• CPC Class Codes: G01P 21/00 Testing or calibrating of apparatus or devices covered by the preceding groups

Abstract

Systems and methods described herein relate to the correction of positional vector-valued sensors using a variety of calibration processes including fixed-angle calibration, known-angle calibration, ortho-calibration and 3-axis gimbal calibration further including various weighting schemes to provide fine-tuned functions or interpolated data which may be used for real-time sensor correction calculation or to populate a look-up table of corrected values.

Claims

1. A sensor calibration system comprising:

a vector-value sensor;

a special-purpose computer machine configured to automatically calculate a set of vector corrections in response to receiving, as computer input, a set of sensed vectors from said vector-value sensor wherein said computer machine is further configured to calculate a final correction vector by;

in response to placing said vector-value sensor in a prime orientation;

recording, in a computer memory, a prime sensed vector;

in response to rotating said vector-value sensor a first known angle away from said prime orientation;

recording, in said computer memory, a first sensed vector;

in response to rotating said vector-value sensor a second known angle away from said prime orientation;

recording, in said computer memory, a second sensed vector;

in response to rotating said vector-value sensor through “

n”

known angles away from said prime orientation;

recording, in said computer memory, through “

n”

sensed vector(s);

calculating a set of calculated vectors by;

calculating a first calculated vector by rotating the prime sensed vector by said first known angle away from said prime orientation;

calculating a second calculated vector by rotating the prime sensed vector by said second known angle away from said prime orientation;

calculating through “

n”

calculated vector(s) by rotating the prime sensed vector by each of said “

n”

known angle(s) away from said prime orientation;

calculating a set of first, second, through “

n”

vector corrections (cv_i) by subtracting;

said first sensed vector from said first calculated vector;

said second sensed vector from said second calculated vector;

each of said “

n”

sensed vectors from each of said “

n”

calculated vector(s); and

calculating said final correction vector, for an input vector from said vector-valued sensor, using said set of vector corrections.

2. A sensor calibration system as claimed in claim 1 wherein said final correction vector is calculated by further weighting an average of said set of first, second, through “

n”

vector corrections wherein a proximity value more heavily weights vectors more proximate to said input vector than less proximate vectors.

3. A sensor calibration system as claimed in claim 2 wherein for each sensed vector (s_i) a weight (w_i) is calculated using the formula:

w_i=((v*s_i)+1)^p and further wherein v represents said input vector and p adjusts how closely said final correction vector should be affected by a set of nearby vectors.

4. A sensor calibration system as claimed in claim 3 wherein p equals 20.

5. A sensor calibration system as claimed in claim 3 wherein:

each of said weights (w_i) is summed into weight_total;

each of said weights (w_i) is divided by weight_total; and

said final correction vector (cv_final) is calculated using a cv_final formula comprising

cv_final=Σ

cv_i*w_i.

6. A sensor calibration system as claimed in claim 5 wherein said computer machine calculates said final corrected vector using a set of interpolated vector corrections from a computer memory.

7. A sensor calibration system as claimed in claim 1 wherein said weighted average of said set of first, second, through “

n”

vector corrections is performed using a distance-based weighting formula.

8. A sensor calibration system as claimed in claim 1 further comprising a ratchet platform which rotates said vector-value sensor.

9. A sensor calibration system as claimed in claim 1 further comprising a 3-axis gimbal which samples and records data from said vector-value sensor and said gimbal'"'"'s orientation.

10. A sensor calibration system as claimed in claim 1 further configured to calculate said final correction vector for said input vector by calculating a weighted average of said set of first, second, through “

n”

vector corrections, wherein a proximity value weights more proximate vectors more heavily than less proximate vectors.

11. A sensor calibration system as claimed in claim 10 wherein each of said known angles divides into 360 evenly.

12. A sensor calibration system as claimed in claim 11 further comprising a bracket, wherein, for each rotation of said vector-value sensor, said vector-value sensor is placed in said bracket designed to provide consistent angle rotation.

13. A sensor calibration system as claimed in claim 1 wherein said vector-value sensor comprises six faces and said final correction vector for said input vector is calculated by:

recording said set of sensed vectors for each of said six faces wherein each of said sensed vectors is recorded in response to rotating said vector-value sensor about each of said six faces'"'"' normal and further wherein each of said six faces are similarly situated for gathering said set of sensed vectors; and

calculating said set of calculated vectors for each of said six faces; and

calculating said final correction vector for a given vector by calculating a weighted average of said set of first, second, through “

n”

vector corrections for each of said six faces wherein a proximity value weights more proximate vectors more heavily than less proximate vectors.

14. A sensor calibration system as claimed in claim 13 wherein a plurality of final correction vectors are interpolated from a plurality of angles and stored in a computer memory and wherein said computer machine accesses said computer memory to retrieve a final correction vector in response to receiving as computer input said input vector from said vector-value sensor.

15. A sensor calibration system comprising:

a vector-value sensor selected from the group consisting of a magnetometer and a accelerometer;

a special purpose computer machine configured to automatically calculate a final correction vector for an input vector by;

in response to placing said vector-value sensor in a prime orientation, recording a prime sensed vector;

in response to rotating said vector-value sensor a first known angle away from said prime orientation, recording, in computer memory, a first sensed vector;

in response to rotating said vector-value sensor a second known angle away from said prime orientation, recording, in computer memory, a second sensed vector;

in response to rotating said vector-value sensor through “

n”

known angle(s) away from said prime orientation, recording, in computer memory, through an “

n”

sensed vector;

calculating a set of calculated vectors by;

calculating a first calculated vector by rotating the prime sensed vector by said first known angle away from said prime orientation;

calculating a second calculated vector by rotating the prime sensed vector by said second known angle away from said prime orientation;

calculating through “

n”

calculated vector(s) by rotating the prime sensed vector by each of said “

n”

known angle(s) away from said prime orientation;

calculating a set of first, second through “

n”

vector corrections (cv_i) by subtracting each of said first, second through “

n”

sensed vectors from each of said calculated vectors where said sensed vectors and said calculated vectors share said known angle;

calculating said final correction vector for said input vector by

taking a weighted average of said set of first, second, through “

n”

vector corrections wherein a proximity value (p) weights more proximate vectors more heavily than less proximate vectors,

for each sensed vector (s_i) a weight (w_i) is calculated in relation to said input vector (v) using the formula;

w_i=((v*s_i)+1)^p,

each of said weights calculated is summed into weight_total;

each of said weights (w_i) is divided by weight weight_total; and

said final correction vector (cv_final) is calculated by a cv_final formula comprising;

cv_final=Σ

cv_i*w_i.

16. A sensor calibration system as claimed in claim 15 wherein said computer machine interpolates a set of final correction vectors for a plurality of vectors and stores said final correction vectors in a computer memory.

17. A sensor correction system comprising a computer machine further comprising computer-executable instructions to:

receive an input vector reading from a vector-value sensor;

access a computer memory comprising a set of interpolated final correction vectors for a plurality of vector readings;

select an applicable final correction vector;

return said final correction vector as computer machine output.

18. A sensor correction system as claimed in claim 17 wherein said set of interpolated final correction vectors are determined from a set of sensed vectors, in response to rotating said vector-value sensor through at least “

n”

known angles, and a set of calculated vectors, in response to rotating a prime sensed vector through said “

n”

known angles away from a prime orientation and wherein said sensed vectors and said calculated vectors are subtracted from one another, weighted, and normalized.

19. A sensor correction system as claimed in claim 18 wherein a given final correction vector is calculated using a cv_final formula comprising:

cv_final=Σ

cv_i*w_i wherein cv_final is said final correction vector, cv_i represents a correction vector associated with each angle rotation, and w_i represents a normalized weight factor.

20. A sensor correction system as claimed in claim 19 wherein a proximity value weights more proximate vectors more heavily than less proximate vectors.