Cordless inertial vehicle navigation

• US 20120053834A1
• Filed: 08/25/2010
• Published: 03/01/2012
• Est. Priority Date: 08/25/2010
• Status: Active Grant

• Current Assignee: Trimble Navigation Limited (Trimble Inc.)
• Original Assignee: Trimble Navigation Limited (Trimble Inc.)
• Inventors: Loomis, Peter Van Wyck
• Granted Patent: US 8,406,996 B2
• Time in Patent Office: Days
• US Class Current: 701/510
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

Inertial navigation systems for wheeled vehicles with constrained motion degrees of freedom are described.

Claims

1. A method for estimating position, heading and speed of a wheeled vehicle, the method comprising:

providing a position sensor, an altimeter, a pitch rate gyro, a yaw rate gyro, a longitudinal accelerometer and a processor; and

,

executing a Kalman filter in the processor to estimate position, heading and speed based on;

altitude, pitch rate, yaw rate and longitudinal acceleration information from the altimeter, pitch rate gyro, yaw rate gyro and longitudinal accelerometer, respectively, and position information from the position sensor when position information is available;

wherein,

the Kalman filter does not require lateral acceleration, vertical acceleration or roll rate.

2. The method of claim 1 further comprising executing a Kalman filter in the processor to calibrate altimeter bias, pitch rate gyro bias, yaw rate gyro bias and longitudinal accelerometer bias when position sensor information is available.

3. The method of claim 1 further comprising executing a Kalman filter in the processor to estimate the speed of the vehicle based on altitude, pitch rate and longitudinal acceleration when position sensor information is unavailable.

4. The method of claim 1 further comprising applying a correction to the longitudinal acceleration information based on the distance between the longitudinal accelerometer and a pivot point of the wheeled vehicle.

5. The method of claim 1 further comprising calibrating vertical axes of the pitch rate gyro, yaw rate gyro and longitudinal accelerometer by determining the average direction of maximum acceleration.

6. The method of claim 1 further comprising calibrating longitudinal axes of the pitch rate gyro, yaw rate gyro and longitudinal accelerometer by matching changes in velocities measured by the accelerometer and by a GNSS receiver.

7. The method of claim 6 further comprising calibrating longitudinal axes of the pitch rate gyro and longitudinal accelerometer by matching changes in velocities measured by the accelerometer and by a combination of the GNSS receiver and the yaw rate gyro.

8. The method of claim 1 wherein the position sensor is a GNSS receiver.

9. The method of claim 1 wherein the altimeter comprises a MEMS pressure sensor.

10. The method of claim 1 wherein the pitch rate and yaw rate gyros are MEMS gyros.

11. The method of claim 1 wherein the longitudinal accelerometer is a MEMS accelerometer.

12. A navigation system comprising:

a position sensor and an altimeter;

a pitch rate gyro and a yaw rate gyro;

a longitudinal accelerometer; and

,

a processor that;

receives altitude, pitch rate, yaw rate and longitudinal acceleration information from the altimeter, pitch rate gyro, yaw rate gyro and longitudinal accelerometer, respectively;

receives position information from the position sensor when position information is available; and

,

executes a Kalman filter to estimate position, heading and speed of a wheeled vehicle based on available information without requiring lateral acceleration, vertical acceleration or roll rate.

13. The system of claim 12 wherein the processor further executes a Kalman filter to calibrate altimeter bias, pitch rate gyro bias, yaw rate gyro bias and longitudinal accelerometer bias when position sensor information is available.

14. The system of claim 12 wherein the processor further executes a Kalman filter to estimate the speed of the vehicle based on altitude, pitch rate and longitudinal acceleration when position sensor information is unavailable.

15. The system of claim 12 wherein the processor further applies a correction to the longitudinal acceleration information based on the distance between the longitudinal accelerometer and a pivot point of the wheeled vehicle.

16. The system of claim 12 wherein the processor further calibrates vertical axes of the pitch rate gyro, yaw rate gyro and longitudinal accelerometer by determining the average direction of maximum acceleration.

17. The system of claim 12 wherein the processor further calibrates longitudinal axes of the pitch rate gyro, yaw rate gyro and longitudinal accelerometer by matching changes in velocities measured by the accelerometer and by a GNSS receiver.

18. The system of claim 17 wherein the processor further calibrates longitudinal axes of the pitch rate gyro and longitudinal accelerometer by matching changes in velocities measured by the accelerometer and by a combination of the GNSS receiver and the yaw rate gyro.

19. The system of claim 12 wherein the position sensor is a GNSS receiver.

20. The system of claim 12 wherein the altimeter comprises a MEMS pressure sensor.

21. The system of claim 12 wherein the pitch rate and yaw rate gyros are MEMS gyros.

22. The system of claim 12 wherein the longitudinal accelerometer is a MEMS accelerometer.

23. The system of claim 12 further comprising a display that displays the position of the vehicle.

24. The system of claim 12 further comprising a memory that stores position estimates and sensor bias information.

25. The system of claim 12 wherein the system does not include a roll rate gyro.