Aided INS/GPS/SAR navigation with other platforms

• US 7,711,476 B2
• Filed: 10/24/2005
• Issued: 05/04/2010
• Est. Priority Date: 06/23/2005
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Chiou, Kuo-Liang, Rudolph, Kevin E., Chiou, Carroll C.
• Primary Examiner(s): Tran; Khoi
• Assistant Examiner(s): Sriraman; Nikhil
• Application Number:
  US11/257,235
• Publication Number:
  US 20060293853A1
• Time in Patent Office: 1,653 Days
• Field of Search: 701/207, 701/200, 701/225, 701/1, 340/988, 340/991, 340/901, 340/995.25, 340/995.28, 342/357.14, 342/451
• US Class Current: 701/207
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/90 using synthetic aperture techniques , e.g. synthetic aperture radar [SAR] techniques
• CPC Class Codes: G01S 19/21 Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
• CPC Class Codes: G01S 7/40 Means for monitoring or calibrating

Abstract

The need for geo-registered features is avoided by a system for estimating a motion of a first sensor during a time interval. The system has a second sensor where the first sensor and the second sensor sense the same geo-location during the time interval. The first sensor computes a first target location error from sensing the geo-location. The second sensor also computes a second target location error from sensing the geo-location. A data link interconnects the first sensor and the second sensor, the data link transmitting the second target location error computed by the second sensor to the first sensor during the time interval. A processor at the first sensor combines the first target location error and the second target location error in a first sensor observation model, where the sensor observation model is descriptive of the motion of the first sensor. The observation model is used with a Kalman filter to update the position of the first sensor. This combination of the first sensor observation model and the second sensor observation model generates a more accurate target location error at the first sensor. The principle is extended to a plurality of platforms.

Claims

1. A system for estimating an independent motion of a first sensor during a time interval, said system comprising:

a second sensor separated from and not co-located with said first sensor, said first sensor and said second sensor each sensing a same geo-location during said time interval, said first sensor computing a first target location error from sensing said geo-location, said second sensor computing a second target location error from sensing said same geo-location, wherein said same geo-location is remote from and not directly coupled to said first and second sensors and is not pre-registered with nor known in advance by either of said first and second sensors, wherein said first and second sensors have motions independent and different from each other;

a bidirectional data link interconnecting said first sensor and said second sensor, said bidirectional data link transmitting said second target location error from said second sensor to said first sensor during said time interval;

a processor arranged at said first sensor and configured to combine at least said first target location error and said second target location error in a first sensor observation model that determines a combined target location error, said first sensor observation model describing and estimating the motion of said first sensor, said combined target location error reducing a target location error associated with the first sensor,

wherein the system is operable when a Global Positioning Position (GPS) location signal is either jammed or otherwise unavailable to one or more of the first and second sensors.

2. A system as described in claim 1 wherein said first sensor is a synthetic aperture radar.

3. A system as described in claim 1 wherein said first sensor is an infrared sensor.

4. A system as described in claim 1 wherein said first sensor is a sound navigation and ranging (SONAR) sensor.

5. A system as described in claim 1 wherein said first sensor observation model updates a Kalman filter computed by said processor.

16. The system of claim 1, wherein said first sensor observation model comprises an observation matrix and a measurement noise matrix.

17. The system of claim 1, further comprising a third sensor, said third sensor sensing the geo-location during said time interval, said third sensor computing a third target location error from sensing said geo-location;

wherein the data link interconnects each of said first sensor, said second sensor, and said third sensor, said data link transmitting said third target location error from said third sensor to said first sensor during said time interval,

wherein said processor combines said third target location error in said first sensor observation model to determine said combined target location error so as to further reduce the target location error associated with the first sensor.

18. The system of claim 1, further comprising a plurality of N sensors, wherein N is greater than two, wherein each of said N sensors sense the geo-location during said time interval and compute an associated target location error that is linked to at least the first sensor via the data link.

22. The system of claim 1, wherein said combined target location error provides an estimated target position that is more accurate than target positions associated with either of said first and said second sensors.

6. A system for estimating an independent motion of each sensor of a plurality of at least three spatially separated sensors during a time interval, the system comprising:

each sensor of said plurality of at least three spatially separated sensors sensing a same geo-location during said time interval and generating an associated target location error for said same geo-location, wherein said same geo-location is remote from and not directly coupled to said plurality of at least three spatially separated sensors and is not pre-registered with nor known in advance by any of said plurality of at least three spatially separated sensors, wherein said plurality of at least three spatially separated have motions independent and different from each other;

a bidirectional data link interconnecting all sensors of said plurality of at least three spatially separated sensors, said bidirectional data link transmitting said associated target location error from each sensor of said plurality of at least three spatially separated sensors to each of the other sensors of said plurality of at least three spatially separated sensors during said time interval;

a processor arranged at each sensor of said plurality of at least three spatially separated sensors that combines said target location errors received from said plurality of at least three spatially separated sensors into a combined target location error determined by an associated sensor observation model, said target location errors being received using said bidirectional data link during said time interval, said associated sensor observation model describing and estimating said independent motion of one sensor of the plurality of at least three spatially separated sensors, said combined target location error reducing a target location error associated with said one sensor,

wherein the system is operable when a Global Positioning Position (GPS) location signal is either jammed or otherwise unavailable to one or more of the plurality of at least three spatially separated sensors.

7. A system as described in claim 6 wherein one or more of each sensor of said plurality of sensors is a synthetic aperture radar.

8. A system as described in claim 6 wherein one or more of each sensor of said plurality of sensors is an infrared sensor.

9. A system as described in claim 6 wherein one or more of each sensor of said plurality of sensors is a sound navigation and ranging (SONAR) sensor.

10. A system as described in claim 6 wherein said associated sensor observation model updates a Kalman filter computed by said processor.

23. The system of claim 6, wherein said combined target location error provides an estimated target position that is more accurate than target positions associated with any one of the at least three spatially separated sensors.

24. The system of claim 6, wherein each sensor of a plurality of at least three spatially separated sensors is interconnected to each other sensor of the at least three spatially separated sensors via the bidirectional data link.

11. A method for estimating an independent motion of a first sensor during a time interval, said method comprising:

sensing a same geo-location using said first sensor and a second sensor separated from and not co-located with said first sensor during said time interval, wherein said same geo-location is remote from and not directly coupled to said first and second sensors and is not pre-registered with nor known in advance by either of said first and second sensors, wherein the first and second sensors have motions independent and different from each other, and wherein a Global Positioning Position (GPS) location signal is either jammed or otherwise unavailable to one or more of the first and second sensors;

computing a first target location error using said first sensor;

computing a second sensor location error using said second sensor;

interconnecting said first sensor and said second sensor by a bidirectional data link, said bidirectional data link transmitting said second location error from said second sensor to said first sensor during said time interval;

combining said first target location error and said second target location error in a first sensor observation model that determines a combined target location error, said first sensor observation model describing and estimating the independent motion of said first sensor; and

reducing the first target location error associated with said first sensor using said combined target location error.

12. A method as described in claim 11 wherein said first sensor is a synthetic aperture radar.

13. A method as described in claim 11 wherein said first sensor is an infrared sensor.

14. A method as described in claim 11 wherein said first sensor is a sound navigation and ranging (SONAR) sensor.

15. A method as described in claim 11 wherein said sensor observation model updates a Kalman filter.

19. The method of claim 11, further comprising:

computing a third sensor location error associated with a third sensor;

interconnecting said first sensor, said second sensor, and said third sensor using the data link, said data link transmitting said third location error from said third sensor to at least said first sensor during said time interval; and

combining said first target location error and said third target location error in the first sensor observation model to determine said combined target location error, wherein said combined target location error further reduces the target location error associated with the first sensor.

20. The method of claim 11, further comprising computing N sensor location errors associated with N sensors, wherein N is greater than 2;

and linking the computed N sensor location errors to at least the first sensor via the data link.

21. The method of claim 11, wherein said combining said first target location error and said second target location error in a first sensor observation model provides an estimated target position that is more accurate than target positions associated with either of said first and said second sensors.