Distributed kalman filter architecture for carrier range ambiguity estimation

• US 10,564,296 B2
• Filed: 10/16/2017
• Issued: 02/18/2020
• Est. Priority Date: 12/23/2016
• Status: Active Grant

• Current Assignee: U-Blox AG (u-blox Holding AG)
• Original Assignee: U-Blox AG (u-blox Holding AG)
• Inventors: Hide, Christopher David, Parkins, Alexander James
• Primary Examiner(s): Liu, Harry K
• Application Number:
  US15/784,452
• Publication Number:
  US 20180180743A1
• Time in Patent Office: 855 Days
• Field of Search: 34235727
• CPC Class Codes: G01S 19/13 Receivers
• CPC Class Codes: G01S 19/44 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method

Abstract

Methods and apparatus for determining navigation data (124) using carrier range measurements obtained by a GNSS receiver for a plurality of GNSS satellites, the apparatus comprising: a first Kalman filter (100) configured to determine an a posteriori estimate of a first state vector based at least in part on a first set of GNSS measurements (104) obtained by the, and/or a further, GNSS receiver and an a priori estimate of the first state vector, the first state vector comprising carrier range ambiguity values relating to the plurality of GNSS satellites and a position of the, and/or the further, GNSS receiver; and a second Kalman filter (102) configured to determine an a posteriori estimate of a second state vector, which comprises the navigation data (124), based at least in part on a second set of GNSS measurements (106) obtained by the, and/or a further, GNSS receiver, an a priori estimate of the second state vector, and carrier range ambiguity data (126) based on the carrier range ambiguity values determined in the a posteriori estimate of the first state vector.

Claims

1. An apparatus for determining navigation data using carrier range measurements obtained by a GNSS receiver for a plurality of GNSS satellites, the apparatus comprising:

a first Kalman filter configured to determine an a posteriori estimate of a first state vector based at least in part on a first set of GNSS measurements obtained by the, and/or a further, GNSS receiver and an a priori estimate of the first state vector, the first state vector comprising carrier range ambiguity values relating to the plurality of GNSS satellites and a position of the, and/or the further, GNSS receiver; and

a second Kalman filter configured to determine an a posteriori estimate of a second state vector, which comprises the navigation data, based at least in part on a second set of GNSS measurements obtained by the, and/or a further, GNSS receiver, an a priori estimate of the second state vector, and carrier range ambiguity data based on the carrier range ambiguity values determined in the a posteriori estimate of the first state vector.

2. The apparatus according to claim 1, wherein the first Kalman filter is configured to determine the a priori estimate of the first state vector based on at least one of a velocity estimate for the, and/or the further, GNSS receiver and a measure of uncertainty relating to the velocity estimate, each determined by the second Kalman filter.

3. The apparatus according to claim 2, wherein the second Kalman filter is configured to determine the velocity estimate and/or the measure of uncertainty based on data obtained by one or more sensors and that is indicative of motion and/or orientation of the, and/or the further, GNSS receiver.

4. The apparatus according to claim 2, wherein the second Kalman filter is configured to determine the velocity estimate and/or the measure of uncertainty based on the a priori estimate of the second state vector and one or more measurements obtained by one or more sensors and indicative of a speed of the, or the further, GNSS receiver.

5. The apparatus according to claim 1, wherein, when determining the a posteriori estimate of the first state vector, the first Kalman filter is configured to determine estimated first measurement residuals for the first Kalman filter based on second measurement residuals for the second Kalman filter.

6. The apparatus according to claim 5, wherein the first Kalman filter is further configured to estimate the first measurement residuals based on Kalman filter parameters of the second Kalman filter, at least part of the a priori estimate of the second state vector and at least part of the a priori estimate of the first state vector.

7. The apparatus according to claim 1, wherein the first Kalman filter is configured to determine the a posteriori estimate of the first state vector at a first update rate, and wherein the second Kalman filter is configured to determine the a posteriori estimate of the second state vector at a second update rate.

8. The apparatus according to claim 7, wherein the second update rate is greater than the first update rate.

9. The apparatus according to claim 1, wherein the second Kalman filter is configured to determine the a priori estimate of the second state vector based on inertial measurements obtained by one or more inertial sensors and indicative of acceleration and/or angular rate of rotation of the, or the further, GNSS receiver.

10. The apparatus according to claim 1, wherein one of the first or second sets of GNSS measurements comprise at least one GNSS measurement not included in the other of the first or second sets of GNSS measurements.

11. The apparatus according to claim 1, comprising two GNSS receivers, and wherein the first and second sets of GNSS measurements each comprise GNSS measurements obtained by the two GNSS receivers.

12. The apparatus according to claim 1, further comprising first and second processors, wherein the first processor is configured to implement the first Kalman filter and the second processor is configured to implement the second Kalman filter.

13. The apparatus according to claim 1, further comprising an ambiguity resolution module configured to resolve the carrier range ambiguity values determined in the a posteriori estimate of the first state vector to integers, and wherein the carrier range ambiguity data comprises the resolved integer carrier range ambiguity values.

14. The apparatus according to claim 1, wherein the first state vector comprises atmospheric correction values relating to the plurality of GNSS satellites.

15. The apparatus according to claim 14, wherein the carrier range ambiguity data comprises the carrier range ambiguity values and the atmospheric correction values, and wherein the second Kalman filter is configured to adjust the carrier range ambiguity values based on the atmospheric correction values.

16. The apparatus according to claim 14, wherein the first Kalman filter is configured to adjust the carrier range ambiguity values based on the atmospheric correction values, and wherein the carrier range ambiguity data comprises the adjusted carrier range ambiguity values.

17. The apparatus according to claim 1, further comprising one or more further Kalman filters configured to determine an a posteriori estimate of one or more further state vectors based at least in part on further GNSS measurements obtained by the, and/or a further, GNSS receiver and one or more a priori estimates of the one or more further state vectors, the one or more further state vectors comprising further carrier range ambiguity values relating to the plurality of GNSS satellites,

and wherein the carrier range ambiguity data is also based on the further carrier range ambiguity values.

18. A method for determining navigation data using carrier range measurements obtained by a GNSS receiver for a plurality of GNSS satellites, the method comprising:

determining, by a first Kalman filter an a posteriori estimate of a first state vector based at least in part on a first set of GNSS measurements obtained by the, and/or a further, GNSS receiver and an a priori estimate of the first state vector, the first state vector comprising carrier range ambiguity values relating to the plurality of GNSS satellites and a position of the, and/or the further, GNSS receiver; and

determining, by a second Kalman filter an a posteriori estimate of a second state vector, which comprises the navigation data, based at least in part on a second set of GNSS measurements obtained by the, and/or a further, GNSS receiver, an a priori estimate of the second state vector, and carrier range ambiguity data based on the carrier range ambiguity values determined in the a posteriori estimate of the first state vector.

19. A non-transitory computer-readable storage medium storing instructions for determining navigation data using carrier range measurements obtained by a GNSS receiver for a plurality of GNSS satellites, the instructions when executed by one or more processors, cause the one or more processors to perform operations comprising:

determining, by a first Kalman filter an a posteriori estimate of a first state vector based at least in part on a first set of GNSS measurements obtained by the, and/or a further, GNSS receiver and an a priori estimate of the first state vector, the first state vector comprising carrier range ambiguity values relating to the plurality of GNSS satellites and a position of the, and/or the further, GNSS receiver; and

determining, by a second Kalman filter an a posteriori estimate of a second state vector, which comprises the navigation data, based at least in part on a second set of GNSS measurements obtained by the, and/or a further, GNSS receiver, an a priori estimate of the second state vector, and carrier range ambiguity data based on the carrier range ambiguity values determined in the a posteriori estimate of the first state vector.