METHOD AND APPARATUS FOR DIFFERENTIAL GLOBAL POSITIONING SYSTEM (DGPS)-BASED REAL TIME ATTITUDE DETERMINATION (RTAD)

• US 20130069822A1
• Filed: 09/19/2011
• Published: 03/21/2013
• Est. Priority Date: 09/19/2011
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Peck, Stephen R., Wu, Shuwu, Wu, Benjamin
• Granted Patent: US 9,829,582 B2
• Time in Patent Office: Days
• US Class Current: 342/357.24
• CPC Class Codes: G01S 19/04 providing carrier phase data
• CPC Class Codes: G01S 19/073 involving a network of fixed stations
• CPC Class Codes: G01S 19/41 Differential correction, e.g. DGPS [differential GPS]
• CPC Class Codes: G01S 19/44 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled
• CPC Class Codes: G01S 19/53 Determining attitude
• CPC Class Codes: G01S 19/55 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method

Abstract

A differential global positioning system (DGPS) processor can include an almost fixed integer ambiguity (AFIA) module for generating in real-time a multiple dimensional state vector of integer ambiguities and multiple dimensional corrections. The AFIA module can use double difference (DD) measurements for pseudo-range (PR) and carrier phase (CP) pairs generated from at least three global positioning system (GPS) receivers. A DGPS processor can be included in a high data rate real time attitude determination (RTAD) system to achieve high heading accuracy with high integrity.

Claims

1. A differential global positioning system (DGPS) processor, comprising:

an almost fixed integer ambiguity (AFIA) module for generating, in real-time, a multiple dimensional state vector of integer ambiguities and multiple dimensional corrections using double difference (DD) measurements for pseudo-range (PR) and carrier phase (CP) pairs generated from at least three global positioning system (GPS) receivers.

2. The DGPS processor of claim 1, further comprising:

an attitude module for generating an attitude from the multiple dimensional state vector of the AFIA module.

3. The DGPS processor of claim 1, wherein the multiple dimensional corrections are angle corrections for a set of roll, pitch, and/or yaw angles.

4. The DGPS processor of claim 1, wherein the GPS receivers are rigidly fixed in known positions relative to each other.

5. The DGPS processor of claim 1, further comprising:

a data selection module for receiving GPS data and GPS-aided navigation data and selecting observable GPS data for at least three GPS receivers, wherein the GPS-aided navigation data combines GPS data of each GPS receiver with inertial measurement unit (IMU) data;

a line-of-sight (LOS) module for generating a LOS unit vector for each GPS receiver from the observable GPS data for GPS satellites in view of the GPS receivers;

a single difference (SD) module for generating at least two single difference observables, wherein a single difference observable is the difference between two receiver observables, wherein a receiver observable includes observable GPS data or a LOS unit vector for each receiver; and

a DD module for generating at least two double difference observables, wherein a double difference observable is the difference between SD observables of two GPS satellites.

6. The DGPS processor of claim 5, wherein a number of single difference observables and a number of double difference observables is one less than a number of GPS receivers used to generate observable GPS data.

7. The DGPS processor of claim 1, wherein the AFIA module generates a multiple dimensional observation matrix for at least two PR and CP measurement pairs.

8. The DGPS processor of claim 1, wherein the double difference measurements uses a CP measurement for carrier frequency selected from the group consisting of a single frequency and a narrow-lane (NL) frequency, where NL frequency sums at least two CPs measurements together.

9. A method for determining attitude data in real time, comprising:

generating in real time a multiple dimensional state vector of integer ambiguities and multiple dimensional corrections using double difference (DD) measurements for pseudo-range (PR) and carrier phase (CP) pairs generated from at least three global positioning system (GPS) receivers.

10. The method of claim 9, further comprising after generating the multiple dimensional state vector, generating an attitude from the multiple dimensional state vector.

11. The method of claim 9, further comprising, prior to generating the multiple dimensional state vector:

receiving GPS data and GPS-aided navigation data for at least three GPS receivers, wherein the GPS-aided navigation data combines GPS data of each GPS receiver with inertial measurement unit (IMU) data;

selecting observable GPS data from the GPS data and the GPS-aided navigation data;

generating a line-of-sight (LOS) unit vector for each GPS receiver from the observable GPS data for GPS satellites in view of the GPS receivers;

generating at least two single difference (SD) observables, wherein a single difference observable is the difference between two receiver observables, wherein a receiver observable includes at least one of observable GPS data and a LOS unit vector for each receiver; and

generating at least two double difference (DD) observables, wherein a double difference observable is the difference between SD observables of two GPS satellites.

12. The method of claim 9, wherein the relationship between the multiple dimensional state vector and the double difference (DD) measurements is represented by y=Hx+ε

, where y is a DD measurement vector for n GPS satellites in view and m GPS receivers, H is an observation matrix, x is the multiple dimensional state vector, ands represents the DD measurement error, represented by

13. The method of claim 12, wherein the G_il^j satellite observation matrix is represented by

14. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement the method of claim 9.

15. A system for facilitating real time attitude determination (RTAD), comprising:

a differential global positioning system (DGPS) processor for generating in real time periodic attitude data from global positioning system (GPS) receiver data or GPS-aided navigation data using a multiple dimensional state vector of integer ambiguities and multiple dimensional corrections,

wherein the GPS receiver data is generated from at least three GPS receivers and the GPS-aided navigation data combines GPS data of each GPS receiver with inertial measurement unit (IMU) data, and

the multiple dimensional state vector is generated from at least two pairs of double difference (DD) pseudo-range (PR) and carrier phase (CP) measurements.

16. The system of claim 15, further comprising:

a heading update filter estimator for generating a real time attitude determination (RTAD) by combining periodic attitude data of the DGPS processor with inertial measurement unit (IMU) data, wherein the inertial measurement unit (IMU) data is used to maintain continuity of an attitude between sampling of the periodic attitude data.

17. The system of claim 16, wherein the heading update filter estimator further comprises:

a two state heading filter for correcting an average heading from a low authority inertial filter (LAIF) of an inertial measurement unit with the periodic attitude data and generating a two state heading filter output; and

a multiplexer for combining the two state heading filter output with the GPS-aided navigation data from a full inertial filter (FIF) of the inertial measurement unit.

18. The system of claim 16, further comprising:

a standard GPS and inertial navigation system (INS) processor for generating the GPS-aided navigation data using a full inertial filter (FIF) to combine GPS sensor data with inertial measurement unit (IMU) data for a continuous heading; and

a minimally aided GPS and INS processor for generating an average heading using a low authority inertial filter (LAIF) to combine GPS sensor data with inertial measurement unit (IMU) data.

19. The system of claim 15, further comprising:

a PR smoothing processor for smoothing PR measurements of GPS raw receiver data with the CP measurements to generate the GPS receiver data by estimating a CP bias for a smoothing interval and adding the CP bias to the CP to generate a smoothed unbiased measurement, wherein a bias measurement has measurement ambiguity and an unbiased measurement is an absolute measurement.

20. The system of claim 19, wherein the PR smoothing processor is selected from the group consisting of a single frequency smoothing processor, an iono-free smoothing processor, a divergence free smoothing processor, and combinations thereof.