System and method for estimating sensor errors

• US 6,269,306 B1
• Filed: 06/13/2000
• Issued: 07/31/2001
• Est. Priority Date: 06/13/2000
• Status: Expired due to Fees

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Tech
• Inventors: Pilutti, Thomas Edward, Ibrahim, Faroog
• Primary Examiner(s): Camby, Richard M.
• Application Number:
  US09/592,709
• Time in Patent Office: 413 Days
• Field of Search: 701/27, 701/26, 701/213, 701/214, 701/215, 701/220, 701/221, 706/15, 706/16, 706/22, 706/43, 706/900
• US Class Current: 701/214
• CPC Class Codes: G01C 17/38 Testing, calibrating, or compensating of compasses
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments

Abstract

A system 10 for estimating sensor error. In the preferred embodiment, the system 10 includes a module 12 and a linear neuron 14, and is adapted to accurately estimate scale factor and bias error of a yaw rate sensor within an integrated navigation system.

Claims

1. A system for estimating errors in a first sensor, said system comprising:

a module which is communicatively coupled to said first sensor and to a second sensor, and which includes a first portion which selectively generates a first value based upon a signal received from said first sensor, a second portion which selectively generates a second value based upon a signal from said second sensor, and a third portion which combines said first and second value, effective to generate a third value; and

a linear neuron which is communicatively coupled to said module and which receives said first value and said third value, and which estimates said errors within said first sensor based upon said received first and third values.

2. The system of claim 1 wherein said first sensor comprises a yaw rate sensor.

3. The system of claim 2 wherein said second sensor comprises a global position system sensor.

4. The system of claim 3 wherein said first and second values comprise vehicle heading angle values.

5. The system of claim 4 wherein said errors comprise a scale factor error and a sensor bias error.

6. The system of claim 1 wherein said module is further effective to smooth said second value prior to combining it with said first value.

7. The system of claim 6 wherein said module is further effective to generate statistics related to said first and second values and to combine said first and second value based upon said generate statistics.

8. The system of claim 7 wherein said linear neuron is further effective to communicate said errors to said module which utilizes said errors to generate said statistics.

9. A system for estimating a scale factor and bias error of a yaw rate sensor which is used within an integrated navigation system having a global position system sensor, said system comprising:

a first portion which receives a first signal from said global position system sensor and calculates a global position system heading angle based upon said first signal;

a second portion which receives an integrated navigation system heading angle;

a third portion which combines said global position system heading angle and said integrated navigation system heading angle, effective to generate a combined heading angle; and

a linear neuron which is communicatively coupled to said third portion, which receives said integrated navigation system heading angle and said combined heading angle and which is effective to accurately estimate said scale factor and said bias error based upon said received integrated navigation system heading angle and combined heading angle.

10. The system of claim 9 further comprising:

a fourth portion which is effective to generate first statistics relating to said global position system heading angle; and

wherein said third portion receives said first statistics and combines said global position system heading angle and said integrated navigation system heading angle, based upon said received first statistics.

11. The system of claim 10 wherein said linear neuron communicates said scale factor and bias error to said fourth portion which generates second statistics relating to said integrated navigation system heading angle;

and

wherein said third portion further receives said second statistics and combines said global position system heading angle and said integrated navigation system heading angle, further based upon said received second statistics.

12. The system of claim 11 wherein said first portion is further effective to smooth said global position system heading angle.

13. A method for estimating scale factor and bias of a first sensor which measures a certain attribute and generates a first signal based upon said measured attribute, said method comprising the steps of:

providing a second sensor which measures said attribute and generates a second signal based upon said measured attribute;

selectively generating a first value based upon said first signal;

selectively generating a second value based upon said second signal;

combining said first and second value, effective to generate a third value;

providing a linear neuron;

communicating said first value and said third value to said linear neuron; and

utilizing said linear neuron to estimate said scale factor and bias of said first sensor based upon said received first and third values.

14. The method of claim 13 wherein said first sensor comprises a yaw rate sensor.

15. The method of claim 14 wherein said second sensor comprises a global position system sensor.

16. The method of claim wherein said first and second values comprise vehicle heading angle values.

17. The method of claim 16 further comprising the steps of:

generating certain statistics related to said first and second values; and

utilizing said certain statistics to combine said first and second value.

18. The method of claim 17 further comprising the step of:

smoothing said second value prior to combining it with said first value.

19. The method of claim 18 further comprising the step of:

utilizing said estimated scale factor and bias to generate said certain statistics.