SYSTEMS AND METHODS FOR A HYBRID TRANSITION MATRIX

• US 20080077325A1
• Filed: 09/25/2006
• Published: 03/27/2008
• Est. Priority Date: 09/25/2006
• Status: Abandoned Application

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Vallot, Lawrence C., Bye, Charles T.
• Application Number:
  US11/534,951
• Publication Number:
  US 20080077325A1
• Time in Patent Office: Days
• US Class Current: 701/220
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled

Abstract

Systems and methods for improved state estimates using filter algorithms are provided. In one embodiment, a method for navigating a vehicle comprises executing a filter algorithm having a state transition matrix that calculates an update to a state vector based on a state vector for a previous instance in time; receiving inertial measurement data from at least one inertial sensor; receiving data from at least one navigation aid; monitoring for the existence of one or more conditions based on a known error characteristic of the at least one inertial sensor; when the one or more conditions exist, calculating at least one element of the one or more elements of the state transition matrix based on the data from the at least one navigation aid; and when the one or more conditions do not exist, calculating the one or more elements of the state transition matrix based on inertial measurement data.

Claims

1. A navigation system for a vehicle, the system comprising:

at least one inertial sensor;

at least one navigation aid;

a processor adapted to receive inertial measurement data from the at least one inertial sensor and navigation aid data from the at least one navigation aid, the processor further adapted to implement a filter algorithm having a state transition matrix that calculates an update to a state vector based on a state vector for a previous instance in time; and

wherein the processor is further adapted to selectively calculate one or more elements of the state transition matrix using the inertial measurement data or the navigation aid data based on a known error characteristic of the at least one inertial sensor or the at least one navigation aid.

2. The system of claim 1, wherein the filter algorithm implements one of a Kalman filter, a fast Kalman filter (FKF), an extended Kalman filter (EKF), and an unscented Kalman filter (UKF).

3. The system of claim 1, wherein the processor is further adapted to implement a navigation algorithm that calculates a navigation solution based on the inertial measurement data from the at least one inertial sensor;

and

wherein the filter algorithm is further adapted to calculate one or more incremental corrections to the inertial measurement data and provide the one or more incremental corrections to the navigation algorithm.

4. The system of claim 3, wherein the navigation solution includes estimates of one or more of a position of the vehicle, a velocity of the vehicle, and an attitude of the vehicle.

5. The system of claim 3, wherein the filter algorithm is further adapted to receive navigation solution data from the navigation algorithm and calculate the one or more incremental corrections to the inertial measurement data based on the state transition matrix and the navigation solution data.

6. The system of claim 1, wherein the at least one navigation aid includes one or more of a GNSS receiver, a barometric altimeter, and a radar velocity sensor.

7. The system of claim 1, wherein the filter algorithm is adapted to monitor for the existence of one or more operating conditions based on the known error characteristics of the at least one inertial sensor, wherein when the one or more operating conditions exist, the filter algorithm is adapted to calculate at least one element of the one or more elements of the state transition matrix based on the navigational aid data.

8. The system of claim 7, wherein when the one or more operating conditions do not exist, the filter algorithm is adapted to calculate the one or more elements of the state transition matrix based on the inertial measurement data or the navigation aid data.

9. The system of claim 7, wherein when the one or more operating conditions are based on one or more of a predetermined level of vibration, a predetermined frequency range of vibrations, a degree of change in a vibration over time, a value of an element of the state transition matrix, and a value of an element of a state vector.

10. A method for navigating a vehicle, the method comprising:

executing a filter algorithm having a state transition matrix that calculates an update to a state vector based on a state vector for a previous instance in time;

receiving inertial measurement data from at least one inertial sensor;

receiving data from at least one navigation aid;

monitoring for the existence of one or more conditions based on a known error characteristic of the at least one inertial sensor or the at least one navigation aid;

when the one or more conditions exist, calculating at least one element of the one or more elements of the state transition matrix based on the data from the at least one navigation aid; and

when the one or more conditions do not exist, calculating the one or more elements of the state transition matrix based on the inertial measurement data.

11. The method of claim 10, wherein the filter algorithm implements one of a Kalman filter, a fast Kalman filter (FKF), an extended Kalman filter (EKF), and an unscented Kalman filter (UKF).

12. The method of claim 10, further comprising:

calculating one or more incremental corrections to the inertial measurement data using the filter algorithm; and

calculating a navigation solution based on the inertial measurement data from the at least one inertial sensor and the one or more incremental corrections to the inertial measurement data.

13. The method of claim 12, wherein calculating a navigation solution comprises calculating one or more of a position estimate, a velocity estimate, and an attitude estimate.

14. The method of claim 10, wherein receiving data from at least one navigation aid further comprises receiving data from one or more of a GNSS receiver, a barometric altimeter, and a radar velocity sensor.

15. The method of claim 10, wherein monitoring for the existence of one or more conditions further comprises monitoring for a predetermined level of vibration, monitoring for a predetermined frequency range of vibrations, monitoring for a degree of change in a vibration over time, monitoring a value of an element of the state transition matrix, and monitoring a value of an element of a state vector.

16. A computer readable medium having computer-executable instructions for performing a navigation method using a filter algorithm having a state transition matrix, method comprising:

calculating an update to a state vector based on a product of a state vector for a previous instance in time multiplied by the state transition matrix;

receiving inertial measurement data from at least one inertial sensor;

receiving data from at least one navigation aid; and

selectively calculating one or more elements of the state transition matrix using one of the inertial measurement data or the data from the at least one navigation aid based on a known error characteristic of the at least one inertial sensor or the at least one navigation aid.

17. The computer readable medium of claim 16, wherein selectively calculating one or more elements of the state transition matrix comprises:

monitoring for the existence of one or more conditions based on the known error characteristics of the at least one inertial sensor or the ate least one navigation aid; and

when the one or more conditions do not exist, calculating the one or more elements of the state transition matrix based on the inertial measurement data.

18. The computer readable medium of claim 16, further comprising:

when the one or more conditions exist, calculating at least one element of the one or more elements of the state transition matrix based on the data from the at least one navigation aid.

19. The computer readable medium of claim 16, further comprising:

calculating one or more incremental corrections to the inertial measurement data using the filter algorithm; and

calculating a navigation solution based on the inertial measurement data from the at least one inertial sensor and the one or more incremental corrections to the inertial measurement data.

20. The computer readable medium of claim 16, wherein when the one or more conditions are based on one or more of a predetermined level of vibration, a predetermined frequency range of vibrations, a degree of change in a vibration over time, a value of an element of the state transition matrix, and a value of an element of a state vector.