Ultra-tightly coupled GPS and inertial navigation system for agile platforms

• US 20070118286A1
• Filed: 11/23/2005
• Published: 05/24/2007
• Est. Priority Date: 11/23/2005
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Wang, Hanching, Detterich, Bruce
• Granted Patent: US 7,579,984 B2
• Time in Patent Office: Days
• US Class Current: 701/213
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01S 19/21 Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

An Ultra-Tightly Coupled GPS-inertial navigation system for use in a moving agile platform includes a range residual extractor that uses best curve fitting of a third order polynomial for estimating range residual. The curve-fitted residual is used to update an error Kalman filter. The error Kalman filter includes correction for navigation solution, and IMU and GPS parameters. The navigation solution together with GPS parameter corrections are used in a Tracking Predictor to generate high-sampling-rate carrier and code replicas. The curve-fitting error covariance indicates signal to noise ratio for the tracked GPS signal and may be used for early indication of interference or jamming.

Claims

1. A method for evaluating a relative range parameter as a function of time, the relative range parameter representing one or more range aspects between a first object and a second object moving relative to each other, said method comprising:

(a) receiving a signal at said first object from said second object;

(b) sampling at least one relative phase signal representing phase between said received signal and a replica signal produced by said first object;

(c) applying a curve fitting algorithm to said at least one relative phase signal; and

(d) determining the relative range parameter form use of said curve fitting algorithm.

2. The method of claim 1 wherein said relative range parameter is selected from the group consisting of:

a relative range, a derivative of a relative range, or a combination of both a relative range and a derivative of said relative range.

3. The method of claim 1 wherein:

said first object is an agile platform;

said second object is a GPS space vehicle; and

said signal is a GPS signal comprising at least one pseudo-random code sequence.

4. The method of claim 1 wherein said relative phase is a relative carrier phase between a carrier phase of said signal and a carrier phase of said replica signal.

5. The method of claim 1 wherein said relative phase is a relative code phase between a code phase of said signal and a code phase of said replica signal.

6. The method of claim 1 wherein said relative phase is a combination of a relative carrier phase between a carrier phase of said signal and a carrier phase of said replica signal, and a relative code phase of said signal and a code phase of said replica signal.

7. The method of claim 1 wherein said curve fitting algorithm uses at least one technique selected from the group consisting of:

an Nth order polynomial fit, a spline fit, a Fourier series fit, and a Tchebychev fit.

8. The method of claim 1 wherein said curve fitting algorithm is an Nth order polynomial fit, wherein m are samples of said at least one relative phase and, wherein m is greater than N.

9. The method of claim 8 wherein said curve fitting algorithm uses m samples of said relative phase, where m is selected for having a matching output sampling rate to a predefined EKF input rate.

10. The method of claim 1 wherein said curve fitting algorithm uses said at least one relative phase with backward running time.

11. A method for displaying or otherwise defining a relative range as a function of time between a first object and a second object moving relative to each other comprising:

(a) receiving a signal transmitted from the second object, wherein said signal comprises an embedded code stream;

(b) measuring at least one relative phase between said embedded code stream and a replica code steam produced by said first object;

(c) applying a curve fitting algorithm to said measured relative phase; and

(d) displaying or otherwise defining the relative range using results of said applying of the curve fitting algorithm.

12. A method for predicatively producing a first replica signal in an ultra-tightly coupled navigation system comprising:

(a) propagating said first replica signal a half-step ahead of a current time;

(b) receiving a data set including an integrated navigation solution, a space vehicle ephemeris, and at least one EKF correction;

(c) translating said data set into a second replica signal.

(d) computing a time-matched residual between said first replica signal and said second replica signal; and

(e) using said time-matched residual to update said propagating of the first replica signal.

13. The method of claim 12, wherein said first and said second replica signals each include a respective carrier replica signal.

14. The method of claim 12, wherein said first and said second replica signals each include a respective code replica signal.

15. The method of claim 12 wherein said first and said second replica signals are each a combination of a carrier replica signal and a code replica signal.

16. The method of claim 12 wherein each signal of said first and said second replica signals has a phase and a Doppler shift that are respective functions of time.

17. The method in claim 12 wherein said propagating of said first replica is performed at a first sampling rate equal to or higher than a second sampling rate of said integrated navigation solutions.

18. The method of claim 12 wherein said propagating of said first replica is performed at a first sampling rate significantly higher than a second sampling rate of said integrated navigation solutions.

19. The method in claim 12 wherein said EKF corrections contains at least one KF state.

20. The method of claim 19 wherein said KF state is selected from the group consisting of a clock bias, a bias drift corrections, an atmospheric propagation delay correction and an antenna moment arm correction.

21. A method for tracking an incoming GPS signal in an ultra-tightly-coupled GPS/Inertia navigation system comprising:

(a) demodulating received GPS signals using a carrier replica signal in a first stage carrier wipe-off, wherein said carrier replica signal is computed at least in part with a clock drift signal estimated by an EKF, said first stage carrier wipe-off generating an in-phase signal and a quadrature signal;

(b) cross-correlating each of said in-phase and said quadrature signals with an early, a prompt, and a late code replica signals to generate a first set of correlated early, prompt and late data; and

(c) performing a phase rotation on said first set of correlated early, prompt, and late data in a second stage carrier wipe-off, wherein said phase rotation produces a second set of correlated early, prompt, and late data;

(d) performing an average-down on said second set of correlated early, prompt, and late data in a second stage carrier wipe-off, said average-down produces a third set of correlated early, prompt and late data at an output sampling rate compatible with an input sampling rate of an RRE.; and

(e) processing said third set of correlated early, prompt and late data in an RRE, to produce a relative range parameter for facilitating the tracking of said incoming GPS signal.

22. The method of claim 21 further comprising the steps of:

(f) producing an integrated navigation solution from an INM;

(g) processing said relative range parameter of step e in an EKF to produce at least one EKF correction;

(h) processing said integrated navigation solution of step f, a space vehicle ephemeris, and said EKF corrections of step g, in a predictor to produce a replica signal to track said incoming GPS signal.

23. The method of claim 22 wherein said replica signal of step (h) is a code replica or a carrier replica signal.

24. A method for compensating a navigation solution affected by a sensor latency in a GPS-inertial navigation system comprising:

(a) estimating said sensor latency; and

(b) compensating said navigation solution by applying said sensor latency.

25. The method of claim 24 wherein said sensor latency includes an inertial sensor latency.

26. The method of claim 24 wherein said compensating step includes compensating at least one of a velocity, a position, and an attitude of said navigation solution.

27. A method for estimating time synchronization error in a GPS-Inertial navigation system comprising:

(a) receiving an integrated navigation solution and a GPS measurement;

(b) computing a time-matched GPS measurement residual using said integrated navigation, said GPS measurement, and a space vehicle ephemeris;

(c) modeling said time synchronization error as a Kalman filter state in a Kalman filter; and

(d) updating said time synchronization error using said time-matched GPS measurement residual and said Kalman filter.

28. The method of claim 27 wherein said time synchronization error is a result of at least one sensor latency.

29. The method of claim 27 wherein said Kalman filter includes clock bias and drift as states.

30. The method of claim 27 wherein said Kalman filter includes navigation errors and sensor parameter errors as states.

31. A method for compensating a time synchronization error in an ultra-tightly coupled GPS/Inertia navigation system comprising:

(a) receiving a GPS I signal and a GPS Q signal from a correlator;

(b) computing relative phases using said GPS I and Q signals;

(c) fitting said relative phases at a first sampling rate with a pre-determined curve-fitting method to produce a relative range parameter at a second sampling rate lower than said first sampling rate;

(d) processing said relative range parameter through an Error Kalman Filter to produce EKF corrections;

said corrections include said time synchronization error;

(e) applying said time synchronization error to correct an integrated navigation solution from an INM; and

(f) processing said EKF corrections and said integrated navigation solutions through a tracking predictor to produce a replica signal to track a GPS signal.