GNSS signal processing to estimate orbits

• US 8,847,820 B2
• Filed: 09/19/2010
• Issued: 09/30/2014
• Est. Priority Date: 09/19/2009
• Status: Active Grant

• Current Assignee: Trimble Navigation Limited (Trimble Inc.)
• Original Assignee: Trimble Navigation Limited (Trimble Inc.)
• Inventors: Landau, Herbert, Nitschke, Markus
• Primary Examiner(s): LIU, HARRY K
• Application Number:
  US13/393,202
• Publication Number:
  US 20120154210A1
• Time in Patent Office: 1,472 Days
• Field of Search: 342/357.66
• US Class Current: 342/357.66
• CPC Class Codes: G01S 19/04 providing carrier phase data
• CPC Class Codes: G01S 19/20 Integrity monitoring, fault detection or fault isolation of space segment
• CPC Class Codes: G01S 19/258 relating to the satellite constellation, e.g. almanac, ephemeris data, lists of satellites in view
• CPC Class Codes: G01S 19/37 Hardware or software details of the signal processing chain
• CPC Class Codes: G01S 19/43 using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
• CPC Class Codes: G01S 19/44 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method

Abstract

Methods and apparatus are described for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising: obtaining an orbit start vector comprising: a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters, obtaining ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and iteratively correcting the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionospheric-free linear combinations of the epoch are available, to obtain updated orbit start vector values comprising a time sequence of predicted positions and predicted velocities for each satellite over a subsequent interval of epochs and an estimate of Earth orientation parameters.

Claims

1. A method of operating a processor having associated data storage and program code enabling the processor to process a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising:

operating the processor to obtain an orbit start vector comprising;

a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters,

operating the processor to obtain ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and

operating the processor to iteratively correct the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionospheric-free linear combinations of the epoch are available, to obtain updated orbit start vector values comprising a time sequence of predicted positions and predicted velocities for each satellite over a subsequent interval of epochs and an estimate of Earth orientation parameters.

2. The method of claim 1, wherein operating the processor to obtain an orbit start vector comprises:

obtaining an approximate orbit vector for the satellites,

obtaining predicted Earth orbit parameters,

iteratively integrating the approximate orbit vector with the predicted Earth orbit parameters to obtain an orbit prediction for an initial time interval and, with each iteration, adapting the orbit prediction to the approximate orbit vector, and

preparing from the orbit prediction an initial set of values for the orbit start vector and partial derivatives.

3. The method of claim 2, wherein the approximate orbit vector is obtained from one of:

a broadcast satellite navigation message, IGS Ultra-rapid Orbits data, and another source of predicted orbits.

4. The method of claim 2, wherein adapting the orbit prediction to the approximate orbit vector is performed using a least squares approach.

5. The method of claim 2, wherein integrating the approximate orbit vector with the predicted Earth orientation parameters to obtain an orbit prediction is iterated until the orbit prediction remains substantially constant.

6. The method of claim 1, wherein operating the processor to obtain an orbit start vector comprises preparing the orbit start vector from a set of the updated orbit start vector values which is not older than a predetermined time interval.

7. The method of claim 6, wherein the predetermined time interval is not more than a few hours.

8. The method of claim 6, wherein preparing the orbit start vector comprises:

mapping a new orbit start vector from the updated orbit start vector and integrating the new orbit start vector to obtain new values for the orbit start vector.

9. The method of claim 8, wherein integrating the new orbit start vector comprises integrating the new orbit start vector using Earth orientation parameters from the updated start vector values.

10. The method of claim 1, wherein operating the processor to iteratively correct the orbit start vector comprises applying an iterative filter comprising one of:

a Kalman filter, a UD factorized filter, and a Square Root Information Filter.

11. The method of claim 1, wherein the updated orbit state vector further comprises additional parameters for each satellite, and wherein operating the processor to iteratively correct the orbit start vector comprises correcting the additional parameters for each satellite.

12. The method of claim 1, further comprising:

operating the processor to map values from the updated orbit start vector to a current epoch to obtain a current-epoch orbit position and velocity for each satellite.

13. The method of claim 1, wherein the orbit start vector further comprises an ionospheric-free ambiguity per receiver-satellite pair, wherein iteratively correcting the orbit start vector (2635) comprises estimating float values for the ionospheric-free ambiguities, and wherein the method further comprises operating the processor to:

obtain a value for a widelane ambiguity per receiver-satellite pair, the widelane ambiguity values having integer nature,

determine integer-nature values for ambiguities linearly related to the widelane ambiguities and the ionospheric-free ambiguities from the values of the widelane ambiguities and the float values of the ionospheric-free ambiguities,

fix the values of the ionospheric-free ambiguities using the integer-nature values, and

with the values of the ionospheric-free ambiguities fixed, iteratively correct the orbit start vector using a time sequence of the ionospheric-free linear combinations and a set of Earth orbit parameters to obtain an updated orbit start vector comprising a time sequence of predicted positions and predicted velocities for each satellite over an interval of multiple epochs and an estimate of Earth orientation parameters.

14. The method of claim 13, wherein the ambiguities linearly related to the widelane ambiguities and the ionospheric-free ambiguities comprise one of:

narrowlane ambiguities, L1 ambiguities and L2 ambiguities.

15. The method of claim 1, wherein the epochs occur at a rate of about 1 Hz.

16. The method of claim 1, wherein operating the processor to iteratively correct the orbit start vector comprises estimating for each epoch the values of a satellite clock for each satellite and a satellite position for each satellite at each epoch.

17. The method of claim 1, wherein operating the processor to iteratively correct the orbit start vector comprises estimating for each epoch the values of a satellite clock for each satellite, a satellite clock drift, a satellite clock drift rate, and a satellite position for each satellite at each epoch.

18. The method of claim 1, wherein the predicted time sequence of approximate positions for each satellite for at least some of the epochs covers an interval of at least 150 seconds.

19. The method of claim 1, wherein the reference stations are widely distributed about the Earth and the GNSS signal data from each reference station represents code observations and carrier observations of a subset of the GNSS satellites at each epoch.

39. Computer-readable physical storage medium embodying instructions configured, when executed on a computer processing unit, to carry out the method of claim 1.

20. Apparatus for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising:

an element operative to obtain an orbit start vector comprising;

a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters,

an element operative to obtain ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and

an element operative to iteratively correct the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionospheric-free linear combinations of the epoch are available, to obtain updated orbit start vector values comprising a time sequence of predicted positions and predicted velocities for each satellite over a subsequent interval of epochs and an estimate of Earth orientation parameters.

21. The apparatus of claim 20, wherein the element operative to obtain an orbit start vector is operative to obtain an approximate orbit vector for the satellites, obtain predicted Earth orbit parameters, iteratively integrate the approximate orbit vector with the predicted Earth orbit parameters to obtain an orbit prediction for an initial time interval and, with each iteration, to adapt the orbit prediction to the approximate orbit vector, and to prepare from the orbit prediction an initial set of values for the orbit start vector and partial derivatives.

22. The apparatus of claim 21, wherein the approximate orbit vector is obtained from one of:

a broadcast satellite navigation message, IGS Ultra-rapid Orbits data, and another source of predicted orbits.

23. The apparatus of claim 21, wherein the orbit prediction is adapted to the approximate orbit vector using a least squares approach.

24. The apparatus of claim 21, wherein the approximate orbit vector is integrated iteratively with the predicted Earth orientation parameters to obtain an orbit prediction which remains substantially constant.

25. The apparatus of claim 20, wherein the element operative to obtain an orbit start vector is operative to prepare the orbit start vector from a set of the updated orbit start vector values which is not older than a predetermined time interval.

26. The apparatus of claim 25, wherein the predetermined time interval is not more than a few hours.

27. The apparatus of claim 25, wherein the element operative to prepare the orbit start vector is operative to map a new orbit start vector from the updated orbit start vector and to integrate the new orbit start vector to obtain new values for the orbit start vector.

28. The apparatus of claim 27, wherein the new orbit start vector is integrated using Earth orientation parameters from the updated start vector values.

29. The apparatus of claim 20, wherein the element operative to iteratively correct the start vector comprises one of:

a Kalman filter, a UD factorized filter, and a Square Root Information Filter.

30. The apparatus of claim 20, wherein the updated orbit state vector further comprises additional parameters for each satellite, and wherein the element operative to iteratively correct the orbit start vector is operative to correct the additional parameters for each satellite.

31. The apparatus of claim 20, further comprising an element operative to map values from the updated orbit start vector to a current epoch to obtain a current-epoch orbit position and velocity for each satellite.

32. The apparatus of claim 20,

wherein the orbit start vector further comprises an ionospheric-free ambiguity per receiver-satellite pair, and

wherein the element operative to iteratively correct the orbit start vector estimates float values for the ionospheric-free ambiguities,

further comprising an element operative to:

obtain a value for a widelane ambiguity per receiver-satellite pair, the widelane ambiguity values having integer nature,

determine integer-nature values for ambiguities linearly related to the widelane ambiguities and the ionospheric-free ambiguities from the values of the widelane ambiguities and the float values of the ionospheric-free ambiguities,

fix the values of the ionospheric-free ambiguities using the integer-nature values and, with the values of the ionospheric-free ambiguities fixed, and

iteratively correct the orbit start vector using a time sequence of the ionospheric-free linear combinations and a set of Earth orbit parameters to obtain an updated orbit start vector comprising a time sequence of predicted positions and predicted velocities for each satellite over an interval of multiple epochs and an estimate of Earth orientation parameters.

33. The apparatus of claim 32, wherein the ambiguities linearly related to the widelane ambiguities and the ionospheric-free ambiguities comprise one of:

narrowlane ambiguities, L1 ambiguities and L2 ambiguities.

34. The apparatus of claim 20, wherein the epochs occur at a rate of about 1 Hz.

35. The apparatus of claim 20, wherein the element operative to iteratively correct the orbit start vector is operative to estimate for each epoch the values of a satellite clock for each satellite and a satellite position for each satellite at each epoch.

36. The apparatus of claim 20, wherein the element operative to iteratively correct the orbit start vector is operative to estimate for each epoch the values of a satellite clock for each satellite, a satellite clock drift, a satellite clock drift rate, and a satellite position for each satellite at each epoch.

37. The apparatus of claim 20, wherein the predicted time sequence of approximate positions for each satellite for at least some of the epochs covers an interval of at least 150 seconds.

38. The apparatus of claim 20, wherein the reference stations are widely distributed about the Earth and the GNSS signal data from each reference station represents code observations and carrier observations of a subset of the GNSS satellites at each epoch.