GNSS signal processing to estimate MW biases

• US 9,128,176 B2
• Filed: 09/19/2010
• Issued: 09/08/2015
• Est. Priority Date: 06/22/2007
• Status: Active Grant

• Current Assignee: Trimble Navigation Limited (Trimble Inc.)
• Original Assignee: Trimble Navigation Limited (Trimble Inc.)
• Inventors: Seeger, Stephan
• Primary Examiner(s): Phan, Dao
• Application Number:
  US13/392,878
• Publication Number:
  US 20120163419A1
• Time in Patent Office: 1,815 Days
• Field of Search: 701/477, 342/357.27, 342/357.26, 342/357.38, 342/357.46
• US Class Current: 1/1
• 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 code observations and carrier-phase observations at multiple receivers of GNSS signals of multiple satellites over multiple epochs, the GNSS signals having at least two carrier frequencies, comprising: forming an MW (Melbourne-Wübbena) combination per receiver-satellite pairing at each epoch to obtain a MW data set per epoch, and estimating from the MW data set per epoch an MW bias per satellite which may vary from epoch to epoch, and a set of WL (widelane) ambiguities, each WL ambiguity corresponding to one of a receiver-satellite link and a satellite-receiver-satellite link, wherein the MW bias per satellite is modeled as one of (i) a single estimation parameter and (ii) an estimated offset plus harmonic variations with estimated amplitudes.

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 code observations and carrier-phase observations at multiple receivers of GNSS signals of multiple satellites over multiple epochs, the GNSS signals having at least two carrier frequencies, comprising:

operating the processor to form an MW (Melbourne-Wü

bbena) combination per receiver-satellite pairing at each epoch to obtain a MW data set per epoch, the MW data set per epoch including a plurality of MW combinations, each of the plurality of MW combinations formed between one of the multiple receivers and one of the multiple satellites, and

operating the processor to estimate from the MW data set per epoch an MW bias per satellite which may vary from epoch to epoch, and a set of WL (widelane) ambiguities, each WL ambiguity corresponding to one of a receiver-satellite link and a satellite-receiver-satellite link,

wherein the MW bias per satellite is modeled as one of (i) a single estimation parameter and (ii) an estimated offset plus harmonic variations with estimated amplitudes.

2. The method of claim 1, further comprising operating the processor to apply corrections to the GNSS signal data.

3. The method of claim 1, further comprising operating the processor to smooth at least one linear combination of GNSS signal data before estimating the MW bias per satellite.

4. The method of claim 1, further comprising operating the processor to apply at least one MW bias constraint to estimate the MW bias per satellite and the set of WL ambiguities.

5. The method of claim 1, further comprising operating the processor to apply at least one integer WL ambiguity constraint to estimate the MW bias per satellite and the set of WL ambiguities.

6. The method of claim 1, further comprising operating the processor to constrain the WL ambiguities, using a spanning tree (ST) over one of an observation graph and a filter graph.

7. The method of claim 1, further comprising operating the processor to constrain the WL ambiguities, using a minimum spanning tree (MST) on one of an observation graph and a filter graph.

8. The method of claim 7, wherein the minimum spanning tree is based on edge weights, each edge weight derived from receiver-satellite geometry.

9. The method of claim 8, wherein the edge weight is defined with respect to one of (i) a geometric distance from receiver to satellite, (ii) a satellite elevation angle, and (iii) a geometric distance from satellite to receiver to satellite, and (iv) a combination of the elevations under which the two satellites in a single differenced combination are seen at a station.

10. The method of claim 7, wherein the minimum spanning tree is based on edge weights, with each edge weight based on WL ambiguity information, defined with respect to one of (i) difference of a WL ambiguity to integer, (ii) WL ambiguity variance, and (iii) a combination of (i) and (ii).

11. The method of claim 1, further comprising fixing at least one of the WL ambiguities as an integer value to provide at least one fixed WL ambiguity.

12. The method of claim 1, further comprising operating the processor to determine a candidate set of WL integer ambiguity values using the set of WL ambiguities, form a weight for each WL integer ambiguity value in the candidate set, form a weighted combination by summing the weights, and fix at least one WL ambiguity using the weighted combination.

13. The method of claim 11, wherein operating the processor to estimate comprises using the at least one fixed WL ambiguity to estimate the MW bias per satellite.

14. The method of claim 13, wherein operating the processor to estimate comprises applying an iterative filter to the MW data set per epoch and wherein using the at least one fixed WL ambiguity comprises one of (i) putting the at least one fixed WL ambiguity as an observation into the iterative filter, (ii) putting the at least one fixed WL ambiguity as an observation into a copy of the iterative filter generated after each of a plurality of observation updates, and (iii) reducing a number of MW combinations in the MW data set per epoch by the at least one fixed WL ambiguity and putting the resulting reduced MW combinations into a second filter without ambiguity states to estimate at least one MW bias per satellite.

15. The method of claim 1, further comprising shifting at least one MW bias by an integer number of WL cycles.

16. The method of claim 1, further comprising shifting at least one MW bias and its respective WL ambiguity by an integer number of WL cycles.

17. The method of claim 1, wherein the navigation message comprises orbit information.

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

18. Apparatus for processing a set of GNSS signal data derived from code observations and carrier-phase observations at multiple receivers of GNSS signals of multiple satellites over multiple epochs, the GNSS signals having at least two carrier frequencies, comprising:

a combiner operative to form an MW (Melbourne-Wü

bbena) combination per receiver-satellite pairing at each epoch to obtain a MW data set per epoch, the MW data set per epoch including a plurality of MW combinations, each of the plurality of MW combinations formed between one of the multiple receivers and one of the multiple satellites, and

a processor operative to estimate from the MW data set per epoch an MW bias per satellite which may vary from epoch to epoch, and a set of WL (widelane) ambiguities, each WL ambiguity corresponding to one of a receiver-satellite link and a satellite-receiver-satellite link,

wherein the MW bias per satellite is modeled as one of (i) a single estimation parameter and (ii) an estimated offset plus harmonic variations with estimated amplitudes.

19. The apparatus of claim 18, further comprising a receiver operative to apply corrections to the GNSS signal data.

20. The apparatus of claim 18, further comprising a data corrector operative to smooth at least one linear combination of GNSS signal data before the MW bias per satellite is estimated.

21. The apparatus of claim 18, wherein the processor is operative to apply at least one MW bias constraint to estimate the MW bias per satellite and the set of WL ambiguities.

22. The apparatus of claim 18, wherein the processor is operative to apply at least one integer WL ambiguity constraint to estimate the MW bias per satellite and the set of WL ambiguities.

23. The apparatus of claim 18, wherein the processor is operative to use a spanning tree (ST) over one of an observation graph and a filter graph to constrain the WL ambiguities.

24. The apparatus of claim 18, wherein the processor is operative to use a minimum spanning tree (MST) on one of an observation graph and a filter graph to constrain the WL ambiguities.

25. The apparatus of claim 24, wherein the minimum spanning tree is based on edge weights, each edge weight derived from receiver-satellite geometry.

26. The apparatus of claim 25, wherein the edge weight is defined with respect to one of (i) a geometric distance from receiver to satellite, (ii) a satellite elevation angle, and (iii) a geometric distance from satellite to receiver to satellite, and (iv) a combination of the elevations under which the two satellites in a single differenced combination are seen at a station.

27. The apparatus of claim 24, wherein the minimum spanning tree is based on edge weights, with each edge weight based on WL ambiguity information, defined with respect to one of (i) difference of a WL ambiguity to integer, (ii) WL ambiguity variance, and (iii) a combination of (i) and (ii).

28. The apparatus of claim 18, further comprising an ambiguity fixer module operative to fix at least one of the WL ambiguities as an integer value to provide at least one fixed WL ambiguity.

29. The apparatus of claim 18, further comprising an ambiguity searcher module operative to determine a candidate set of WL integer ambiguity values using the set of WL ambiguities, and an ambiguity combiner module operative to form a weight for each WL integer ambiguity value in the candidate set, form a weighted combination by summing the weights, and fix at least one WL ambiguity using the weighted combination.

30. The apparatus of claim 28, wherein the processor is further operative to use the at least one fixed WL ambiguity to estimate the MW bias per satellite.

31. The apparatus of claim 30, wherein the processor is further operative to apply an iterative filter to the MW data set per epoch and to use the at least one fixed WL ambiguity as one of (i) an observation in the iterative filter, (ii) an observation in a copy of the iterative filter generated after each of a plurality of observation updates, and (iii) reduce a number of MW combinations in the MW data set per epoch by the at least one fixed WL ambiguity and put the resulting reduced MW combinations in a second filter without ambiguity states to estimate at least one MW bias per satellite.

32. The apparatus of claim 18, further comprising a bias shifter operative to shift at least one MW bias by an integer number of WL cycles.

33. The apparatus of claim 18, further comprising an internal shifter operative to shift at least one MW bias and its respective WL ambiguity by an integer number of WL cycles.

34. The apparatus of claim 18, wherein the navigation message comprises orbit information.