Inertial GPS navigation system

• US 6,721,657 B2
• Filed: 06/04/2002
• Issued: 04/13/2004
• Est. Priority Date: 06/04/2001
• Status: Active Grant

• Current Assignee: Novatel Incorporated (Hexagon AB)
• Original Assignee: Novatel Incorporated (Hexagon AB)
• Inventors: Neumann, Janet Brown, Williamson, Ian, Ford, Thomas John
• Primary Examiner(s): Cuchlinski, Jr., William A.
• Assistant Examiner(s): Hernandez, Olga
• Application Number:
  US10/162,287
• Publication Number:
  US 20020198656A1
• Time in Patent Office: 679 Days
• Field of Search: 701/213, 701/200, 731/78.R, 342/357.01, 342/357.06, 342/357.12, 342/357.14, 340/988
• US Class Current: 701/213
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 19/44 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
• CPC Class Codes: G01S 19/46 the supplementary measurement being of a radio-wave signal type

Abstract

A receiver that uses a single processor to control a GPS sub-system and an inertial (“INS”) sub-system and, through software integration, shares GPS and INS position and covariance information between the sub-systems. The receiver time tags the INS measurement data using a counter that is slaved to GPS time, and the receiver then uses separate INS and GPS filters to produce GPS and INS position information that is synchronized in time. The GPS/INS receiver utilizes GPS position and associated covariance information in the updating of an INS Kalman filter, which provides updated system error information that is used in propagating inertial position, velocity and attitude. Whenever the receiver is stationary after initial movement, the INS sub-system performs “zero-velocity updates,” to more accurately compensate in the Kalman filter for component measurement biases and measurement noise. Further, if the receiver loses GPS satellite signals, the receiver utilizes the inertial position, velocity and covariance information provided by the Kalman filter in the GPS filters, to speed up GPS satellite signal re-acquisition and associated ambiguity resolution operations.

Claims

1. An inertial/global positioning system (GPS) receiver including:

A. a GPS sub-system for providing correlation measurements associated with signals received from a plurality of GPS satellites;

B. an inertial sub-system for providing inertial measurements from a plurality of accelerometers and gyroscopes;

C. a counter slaved to GPS time;

D. a processor for calculating GPS position based on the correlation measurements and inertial position, velocity and attitude relative to the GPS position based on the inertial measurements, the processor using

GPS position and associated covariance information to control the adverse effects in the inertial calculations of inaccuracies in the inertial sub-system measurements,

inertial position, velocity and associated covariance information to assist in signal re-acquisition operations of the GPS sub-system; and

the count of the counter for time tagging the inertial measurements with GPS time to time synchronize inertial and GPS calculated positions.

2. The inertial/global positioning system receiver of claim 1 wherein the processor further

calculates GPS position relative to a base receiver with a known position, and

uses inertial position and associated covariance information to assist in carrier cycle ambiguity resolution operations that are part of the signal re-acquisition operations.

3. The inertial/global positioning system receiver of claims 2 wherein the processor

processes the GPS correlation measurements using one or more GPS filters, and

processes the inertial measurements using an inertial Kalman filter.

4. The inertial/global positioning system receiver of claim 3 wherein the processor further

uses the inertial Kalman filter to update system error parameters that are used in the calculations of inertial position, velocity and attitude,

calculates an estimated noise level associated with the inertial measurements, and

uses the estimated noise level in the Kalman filter processing and to calculate an initial inertial attitude accuracy estimation.

5. The inertial/global positioning system receiver of claims 4 wherein the processor further

determines when the receiver is stationary after initial movement, and

when the receiver is stationary performs a zero velocity update of the Kalman filter using predetermined velocity values instead of velocity observational values.

6. The inertial/global positioning system receiver of claim 5 wherein the processor uses as the predetermined velocity values the threshold values that are used to determine if the receiver is stationary.

7. The inertial/global positioning system receiver of claim 6 wherein the processor further

performs inertial sub-system start-up routines to initialize the Kalman filter and determine the initial attitude, velocity and position relative to an initial GPS position,

determines if the receiver remains stationary after the completion of the start-up routines and if the receiver is stationary performs updates to the Kalman filter using average specific force values.

8. The inertial/global positioning system receiver of claim 6 wherein the processor further uses an initial rotation matrix to update the Kalman filter if the receiver remains stationary after the completion of the start-up routines.

9. The inertial/global positioning system receiver of claims 8 wherein the processor further performs as part of the start-up routines a frame recognition operation in which the processor sets a reference frame for the receiver in which the y axis of the reference frame is not aligned with the gravity vector.

10. The inertial/global positioning system receiver of claim 9 wherein the processor performs the frame recognition operation by

setting nominal x, y and z axes for the receiver, and

assigning the z-axis to the accelerometer that has an acceleration measurement that is largest in magnitude.

11. The inertial/global positioning system receiver of claim 10 wherein the processor includes in the Kalman filter bias terms associated with estimated measurement biases of the accelerometers and gyroscopes.

12. The inertial/global positioning system receiver of claim 2 wherein the processor during signal re-acquisition operations sets the ambiguity and associated covariance of a GPS floating ambiguity filter to the inertial position and associated covariance.

13. The inertial/global positioning system receiver of claim 2 wherein the processor during signal re-acquisition operations uses the inertial position and the associated covariance to set the ambiguity and associated covariance of a GPS floating ambiguity filter.

14. A method of operating an inertial/global positioning system (GPS) receiver to provide uninterrupted navigation information, the method including the steps of:

A. determining a GPS position and a GPS time-tagged inertial position relative to the GPS position;

B. using the GPS position in the navigation information when a sufficient number of GPS satellites are observable to the receiver and the inertial position when the sufficient number of GPS satellite are not available to the GPS receiver;

C. performing signal re-acquisition operations when the inertial position is used in the navigation information and one or more GPS satellites are again observable to the GPS receiver, the receiver performing the signal re-acquisition operations using the inertial position and associated covariance information and performing ambiguity re-resolution by the setting of ambiguity and associated covariance values of a GPS floating ambiguity filter to values based on the inertial position and associated covariance; and

D. including the GPS position in the navigation information once the receiver has re-acquired the signals from the sufficient number of satellites.

15. A method of operating an inertial/global positioning system (GPS) receiver to provide uninterrupted navigation information, the method including the steps of:

A. determining a GPS position and a GPS time-tagged inertial position relative to the GPS position and updating a Kalman filter using inertial and GPS position information, the GPS time used for tagging a given inertial position being determined by setting the GPS time based on when the receiver receives a first byte of inertial measurement data from which given inertial position is determined;

B. using the GPS position in the navigation information when a sufficient number of GPS satellites are observable to the receiver and the inertial position when the sufficient number of GPS satellite are not available to the GPS receiver;

C. performing signal re-acquisition operations when the inertial position is used in the navigation information and one or more GPS satellites are again observable to the GPS receiver, the receiver performing the signal re-acquisition operations using the inertial position and associated covariance information; and

D. including the GPS position in the navigation information once the receiver has re-acquired the signals from the sufficient number of satellites.

16. The method of claim 15 wherein the step of updating the Kalman filter includes including in a state error vector terms that correspond to an estimated measurement noise level and estimated accelerometer and gyroscope biases.

17. The method of claim 15 wherein the step of updating the Kalman filter includes performing a zero velocity update when the receiver is not moving.

18. The method of claim 17 wherein the step of performing a zero velocity update includes using associated velocity thresholds that are used to determine that the receiver is stationary as observational velocity data.

19. The method of claim 16 wherein the step of updating the Kalman filter includes using average specific forces for updating the Kalman filter when the receiver remains stationary after initialization of the Kalman filter.

20. The method of claim 16 wherein the step of updating the Kalman filter includes using an initial rotational matrix for updating the Kalman filter when the receiver remains stationary after initialization of the Kalman filter.