Method and computer-readable storage medium with instructions for processing data in an internal navigation system

• US 20090254276A1
• Filed: 04/08/2008
• Published: 10/08/2009
• Est. Priority Date: 04/08/2008
• Status: Active Grant

• Current Assignee: ENSCO, Incorporated (Teris LLC)
• Original Assignee: ENSCO, Incorporated (Teris LLC)
• Inventors: Chestnut, Stephen R., Taylor, David W.A., Faulkner, W. Todd
• Granted Patent: US 8,224,575 B2
• Time in Patent Office: Days
• US Class Current: 701/213
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems

Abstract

A method for processing data in an inertial navigation system having a Kalman filter and computer-readable storage medium containing instructions to configure a processor to perform the same. The method produces more accurate estimates of the position, velocity and attitude of the inertial measurement unit. The method is fully automatic and enables zero-velocity updates and fixed-azimuth updates to be performed simultaneously. The method may also include a multi-stage filtering process to filter digital compass data when used in an environment with extraterrestrial magnetic field sources. The method may also include a fixed-lag smoother to improve estimates of the position, velocity and attitude of the inertial measurement unit. The method also may include processes to constrain altitude errors.

Claims

1. A method for processing data in an inertial navigation system having a Kalman filter, the method comprising:

receiving data from an inertial measurement unit;

determining whether the inertial measurement unit is in a zero-velocity condition;

determining whether a predetermined number of data cycles have occurred with a zero-velocity condition present;

performing a zero-velocity update to the Kalman filter if the inertial measurement unit is in a zero-velocity condition;

performing a fixed-azimuth update to the Kalman filter if the predetermined number of data cycles have occurred with a zero-velocity condition present; and

outputting an estimate of the position of the inertial measurement unit.

2. The method of claim 1, comprising substantially simultaneously updating the Kalman filter to represent a zero-velocity condition and updating the Kalman filter to represent a heading rate of zero.

3. The method of claim 1, further comprising:

receiving data from a global positioning system satellite; and

performing a position update to the Kalman filter based on the data received from the global positioning system satellite.

4. The method of claim 1, further comprising:

receiving data from a radio frequency identification tag; and

performing a position update to the Kalman filter based on the data received from the radio frequency identification tag.

5. The method of claim 1, further comprising:

receiving data from a radio frequency ranging transponder; and

performing a position update to the Kalman filter based on the data received from the radio frequency ranging transponder.

6. The method of claim 1, further comprising:

receiving data from a compass;

performing a time change test;

performing a position change test;

calculating a difference between a measured total magnetic field strength and a known local magnetic field strength; and

performing a compass update to the Kalman filter based on data received from the compass.

7. The method of claim 1, further comprising:

performing fixed-lag smoothing.

8. The method of claim 6, further comprising:

analyzing data related to a difference between a magnetic heading and a navigation heading.

9. The method of claim 8, wherein the processing of data from the compass are in real-time.

10. The method of claim 8, further comprising:

analyzing data related to the altitude of the inertial measurement unit; and

performing an altitude update to the Kalman filter based on the data related to the altitude of the inertial measurement unit.

11. A computer-readable storage medium containing instructions to configure a processor to perform a method for processing data in an inertial navigation system having a Kalman filter, the method comprising:

receiving data from an inertial measurement unit;

determining whether the inertial measurement unit is in a zero-velocity condition;

performing a zero-velocity update to the Kalman filter if the inertial measurement unit is in a zero-velocity condition;

determining whether a predetermined number of data cycles have occurred with a zero-velocity condition present;

performing a fixed-azimuth update to the Kalman filter if a user-defined number of data cycles have occurred with a zero-velocity condition present; and

outputting an estimate of the position of the inertial measurement unit.

12. The method of claim 11, comprising substantially simultaneously updating the Kalman filter to represent a zero-velocity condition and updating the Kalman filter to represent a heading rate of zero.

13. The method of claim 11, further comprising:

receiving data from a global positioning system satellite; and

performing a position update to the Kalman filter based on the data received from the global positioning system satellite.

14. The method of claim 11, further comprising:

receiving data from a radio frequency identification tag; and

performing a position update to the Kalman filter based on the data received from the radio frequency identification tag.

15. The method of claim 11, further comprising:

receiving data from a radio frequency ranging transponder; and

performing a position update to the Kalman filter based on the data received from the radio frequency ranging transponder.

16. The method of claim 11, further comprising:

receiving data from a compass;

performing a time change test;

performing a position change test;

calculating a difference between a measured total magnetic field strength and a known local magnetic field strength; and

performing a compass update to the Kalman filter based on data received from the compass.

17. The method of claim 11, further comprising:

performing fixed-lag smoothing.

18. The method of claim 16, further comprising:

analyzing data related to a difference between a magnetic heading and a navigation heading.

19. The method of claim 18, wherein the processing of data from the compass are in real-time.

20. The method of claim 18, further comprising:

analyzing data related to the altitude of the inertial measurement unit; and

performing an altitude update to the Kalman filter based on the data.