Navagation apparatus with improved attitude determination

• US 5,543,804 A
• Filed: 09/13/1994
• Issued: 08/06/1996
• Est. Priority Date: 09/13/1994
• Status: Expired due to Term

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Litton Systems Incorporated
• Inventors: Hsu, David Y., Buchler, Robert J., Brockstein, Allan J.
• Primary Examiner(s): Blum, Theodore M.
• Application Number:
  US08/305,400
• Time in Patent Office: 693 Days
• Field of Search: 342/357, 455/12.1
• US Class Current: 342/357.23
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
• CPC Class Codes: G01S 19/54 using carrier phase measurements; using long or short baseline interferometry

Abstract

The navigation apparatus with improved attitude determination is intended for use on a mobile platform. It combines data from a platform inertial navigation unit and carrier phase data for a plurality of GPS satellite signals received at a plurality of receiving points on the platform for the purpose of obtaining estimates of the navigation states of the platform. The navigation apparatus comprises a processor which computes estimates of the states from inputs comprising (1) one or more measured phase double-differences calculated from the measured satellite signal carrier phases, (2) the estimated position of the platform, (3) the estimated positions of the receiving points, and (4) the positions of the satellites, a phase double-difference being defined as the difference in phase differences for signals received from two satellites and a phase difference being defined as the difference in carrier phase of a satellite signal received at two receiving points. The navigation and attitude determination solution is obtained by means of a Kalman filter process wherein the observables comprise measured phase double-differences and each predicted phase double-difference is obtained by operating on the Kalman state vector with an observation matrix defined by linearizing the equations relating the phase double-difference to the navigation states.

Claims

1. An apparatus for use with a plurality of GPS earth satellites in estimating one or more states of a platform, the platform having a reference point that represents the position of the platform and at least two receiving points corresponding to the locations of antennas for receiving satellite signals, the apparatus comprising:

a processor for computing estimates of the errors in the platform states from inputs comprising (1) one or more measured phase double-differences obtained from signals transmitted by a plurality of satellites, (2) the estimated position of the reference point, (3) the estimated positions of the receiving points relative to the reference point, and (4) the positions of the satellites, a phase double-difference being defined as the difference in phase differences for signals received from two satellites, a phase difference being the difference in carrier phase of a satellite signal received at two receiving points on the platform.

2. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include the platform attitude.

3. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include the platform position in a level coordinate frame.

4. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include the platform altitude.

5. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include each receiving point position.

6. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include a first receiving point position and the position of each remaining receiving point relative to the position of the first receiving point.

7. The apparatus of claim 1 wherein the one or more states for which the processor computes estimates of errors include the position of each receiving point other than a first receiving point relative to the first receiving point.

8. The apparatus of claim 1 further comprising:

a preprocessor which supplies the one or more measured double-differences to the processor, the one or more measured double-differences being determined by the preprocessor from inputs to the preprocessor, the inputs to the preprocessor comprising a plurality of measured phase differences.

9. The apparatus of claim 1 further comprising:

a preprocessor which supplies the one or more measured double-differences to the processor, the one or more measured double-differences being determined by the preprocessor from inputs to the preprocessor, the inputs to the preprocessor comprising the measured carrier phases of signals from a plurality of satellites received at a plurality of receiving points on the platform.

10. The apparatus of claim 1 wherein the processor computes estimates of the errors in the platform states by performing a Kalman filter process.

11. The apparatus of claim 10 wherein the processor in executing the Kalman filter process computes one or more predicted phase double-differences by applying an observation matrix to a state vector, the states in the state vector contributing to the predicted phase double-difference including platform attitude, platform position, computer azimuth, and the positions of the platform receiving points relative to one of the receiving points that serves as a reference point.

12. The apparatus of claim 1 wherein the inputs used by the processor in computing estimates of the errors in the platform states include (1) measured pseudoranges to the satellites and (2) satellite clock errors.

13. The apparatus of claim 12 wherein the inputs to the processor include an estimate of the platform velocity and measured delta ranges to the satellites, the one or more states for which the processor computes estimates of errors including the platform position in a level coordinate frame.

14. The apparatus of claim 13 wherein the one or more states for which the processor computes estimates of errors include the platform altitude.

15. The apparatus of claim 14 wherein the one or more states for which the processor computes estimates of errors include the platform velocity.

16. The apparatus of claim 15 further comprising:

a preprocessor which supplies platform position, velocity, and attitude to the processor, the platform position, velocity, and attitude being determined by the preprocessor from inputs to the preprocessor, the inputs to the preprocessor being the measured acceleration and measured angular rotation rate of the platform.

17. The apparatus of claim 16 wherein the one or more states for which the processor computes estimates of errors include bias, scale factor, and misalignment for each accelerometers and bias, scale factor, and misalignment for each gyro, the source of the measured platform acceleration being a plurality of accelerometers, the source of the measured platform angular rotation rate being a plurality of gyros.

18. The apparatus of claim 17 wherein the preprocessor utilizes the estimates by the processor of the errors in bias, scale factor, and misalignment for each accelerometers and bias, scale factor, and misalignment for each gyro to correct the input acceleration and angular rotation rate data.

19. The apparatus of claim 16 wherein the preprocessor utilizes the estimates by the processor of the errors in platform velocity and attitude to correct the preprocessor outputs of platform velocity and attitude.

20. The apparatus of claim 14 further comprising:

a preprocessor which supplies platform altitude to the processor, the platform altitude being obtained by the preprocessor from an input to the preprocessor, the input to the preprocessor being the measured altitude of the platform.

21. The apparatus of claim 20 wherein the one or more states for which the processor computes estimates of errors include bias and scale factor for an altimeter, the source of the measured platform altitude being the altimeter.

22. The apparatus of claim 21 wherein the preprocessor utilizes the estimates by the processor of the errors in bias and scale factor for the altimeter to correct the input altitude data.

23. The apparatus of claim 15 wherein the one or more states for which the processor computes estimates of errors include the user clock bias and the user clock rate bias, the user clock being the time reference utilized by the source of the pseudorange and delta range data supplied to the processor.

24. The apparatus of claim 23 wherein the processor computes estimates of the errors in the platform states by performing a Kalman filter process.

25. A method of using a plurality of GPS earth satellites for estimating one or more states of a platform, the platform having a reference point that represents the position of the platform and at least two receiving points corresponding to the locations of antennas for receiving satellite signals, the method comprising the steps:

computing estimates of the errors in the platform states from inputs comprising (1) one or more measured phase double-differences obtained from signals transmitted by a plurality of satellites, (2) the estimated position of the reference point, (3) the estimated positions of the receiving points relative to the reference point, and (4) the positions of the satellites, a phase double-difference being defined as the difference in phase differences for signals received from two satellites, a phase difference being the difference in carrier phase of a satellite signal received at two receiving points on the platform, arbitrary input values being used for those quantities for which input values are not supplied.

26. The method of claim 25 wherein the one or more states for which estimates of errors are computed include the platform attitude.

27. The method of claim 25 wherein the one or more states for which estimates of errors are computed include the platform position in a level coordinate frame.

28. The method of claim 25 wherein the one or more states for which estimates of errors are computed include the platform altitude.

29. The method of claim 25 wherein the one or more states for which estimates of errors are computed include each receiving point position.

30. The method of claim 25 further comprising the step:

computing the measured double-differences for input to the "computing estimates" step from a plurality of measured phase differences.

31. The method of claim 25 further comprising the step:

computing the measured double-differences for input to the "computing estimates" step from a plurality of measured carrier phases of signals from a plurality of satellites received at a plurality of receiving points on the platform.

32. The method of claim 25 wherein the estimates are computed by executing a Kalman filter process.

33. The method of claim 32 wherein in executing the Kalman filter process one or more predicted phase double-differences is obtained by applying an observation matrix to a state vector, the states in the state vector contributing to the predicted phase double-difference including platform attitude, platform position, computer azimuth, and the positions of the platform receiving points relative to one of the receiving points that serves as a reference point.

34. The method of claim 25 wherein the inputs used in computing estimates of the errors in the platform states include (1) measured pseudoranges to the satellites and (2) satellite clock errors.

35. The method of claim 34 wherein the inputs used in computing estimates of the errors in the platform states include an estimate of the platform velocity and measured delta ranges to the satellites, the one or more states for which estimates of errors are computed including the platform position in a level coordinate frame.

36. The method of claim 35 wherein the one or more states for which estimates of errors are computed include the platform altitude.

37. The method of claim 36 wherein the one or more states for which estimates of errors are computed include the platform velocity.

38. The method of claim 37 further comprising the step:

computing the position, velocity, and attitude for input to the "computing estimates" step from the measured acceleration and measured angular rotation rate of the platform.

39. The method of claim 38 wherein the one or more states for which estimates of errors are computed include bias, scale factor, and misalignment for each accelerometers and bias, scale factor, and misalignment for each gyro, the source of the measured platform acceleration being a plurality of accelerometers, the source of the measured platform angular rotation rate being a plurality of gyros.

40. The method of claim 39 further comprising the step:

correcting the input acceleration and angular rotation rate data utilizing the computed estimates of the errors in bias, scale factor, and misalignment for each accelerometers and bias, scale factor, and misalignment for each gyro.

41. The method of claim 38 further comprising the step:

correcting the platform velocity and attitude data that serve as inputs to the "computing estimates" step utilizing the computed estimates of the errors in platform velocity and attitude.

42. The method of claim 36 further comprising the step:

obtaining a measured value for the platform altitude from an altimeter;

supplying the measured platform altitude as input to the "computing estimates" step.

43. The method of claim 42 wherein the one or more states for which estimates of errors are computed include bias and scale factor for the altimeter that is the source of the measured altitude.

44. The method of claim 43 further comprising the step:

utilizing the computed estimates of the errors in bias and scale factor for the altimeter to correct the input altitude data.

45. The method of claim 37 wherein the one or more states for which estimates of errors are computed include the user clock bias and the user clock rate bias, the user clock being the time reference utilized by the source of the pseudorange and delta range data.

46. The method of claim 45 wherein the estimates are computed by executing a Kalman filter process.