Multiple sensor processing

• US 7,508,335 B2
• Filed: 11/16/2007
• Issued: 03/24/2009
• Est. Priority Date: 12/20/2006
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Blaha, George A., Stern, Larry L., Cummings, Steven T.
• Primary Examiner(s): Sotomayor; John B
• Application Number:
  US11/941,402
• Publication Number:
  US 20080150787A1
• Time in Patent Office: 494 Days
• Field of Search: 342/59, 342/60, 342/85, 342 95- 97, 342/195
• US Class Current: 342/59
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 7/003 Transmission of data between radar, sonar or lidar systems and remote stations

Abstract

A method of multiple sensor processing includes receiving, at a first sensor system, track data from a second sensor system, comparing track data from the first sensor system to the track data from the second sensor system to determine if a track will be within a field of view of the first sensor system during a time period, determining, at a first sensor system, predicted quality of tracks based on the track data and broadcasting the predicted quality of tracks. The method also includes receiving predicted quality of tracks from the second sensor system and determining a first set of tasks based on the predicted quality of tracks determined by the first sensor system and the predicted quality of tracks received from the second sensor system.

Claims

1. A method of multiple sensor processing comprising:

receiving, at a first sensor system, track data from a second sensor system;

comparing track data from the first sensor system to the track data from the second sensor system to determine if a track will be within a field of view of the first sensor system during a time period;

determining, at a first sensor system, predicted quality of tracks based on the track data from the first and second sensor systems;

broadcasting the predicted quality of tracks;

receiving predicted quality of tracks from the second sensor system; and

determining a first set of tasks based on the predicted quality of tracks determined by the first sensor system and the predicted quality of tracks received from the second sensor system.

2. The method of claim 1, further comprising:

receiving, at the second sensor system, track data from a first sensor system;

comparing track data from the second sensor system to the track data from the first sensor system to determine if a track will be within a field of view of the second sensor system during the time period;

receiving predicted quality of tracks from the first sensor system; and

determining a second set of tasks based on the predicted quality of tracks determined by the second sensor system and the predicted quality of tracks received from the first sensor system.

3. The method of claim 2 wherein the first set of tasks and the second set of task are substantially equivalent.

4. The method of claim 1 wherein determining the first set of tasks comprises determining a set of tasks performed by each sensor system.

5. The method of claim 1 wherein determining the first set of tasks comprises determining a first set of tasks using a tabu algorithm.

6. The method of claim 1 wherein determining a first set of tasks comprises determining utilization of resources.

7. The method of claim 1 wherein determining a first set of tasks comprises determining an embedded resource usage benefit calculation based on the broadcasted track predictions.

8. The method of claim 1 wherein determining the predicted quality of tracks comprises determining quality of track observations of the tracks.

9. The method of claim 8 wherein determining the quality of track observations of the tracks comprises determining kinematic measurement variances of the tracks.

10. The method of claim 1 wherein determining the predicted quality of tracks comprises determining resource costs for the tracks.

11. An article comprising a machine-readable medium that stores executable instructions used in multiple sensor processing, the instructions causing a machine to:

receive, at a first sensor system, track data from a second sensor system;

compare track data from the first sensor system to the track data from the second sensor system to determine if a track will be within a field of view of the first sensor system during a time period;

determine, at a first sensor system, predicted quality of tracks based on the track data from the first and second sensor systems;

broadcast the predicted quality of tracks;

receive predicted quality of tracks from the second sensor system; and

determine a first set of tasks based on the predicted quality of tracks determined by the first sensor system and the predicted quality of tracks received from the second sensor system.

12. The article of claim 11, further comprising instructions causing the machine to:

receive, at the second sensor system, track data from a first sensor system;

compare track data from the second sensor system to the track data from the first sensor system to determine if a track will be within a field of view of the second sensor system during the time period;

receive predicted quality of tracks from the first sensor system; and

determine a second set of tasks based on the predicted quality of tracks determined by the second sensor system and the predicted quality of tracks received from the first sensor system.

13. The article of claim 12 wherein the first set of tasks and the second set of task are substantially equivalent.

14. The article of claim 11 wherein the instructions causing the machine to determine the first set of tasks comprises instructions causing a machine to determine a set of tasks performed by each sensor system.

15. The article of claim 11 wherein instructions causing the machine to determine the first set of tasks comprises instructions causing the machine to determine a first set of tasks using a tabu algorithm.

16. An apparatus used in multiple sensor processing, comprising:

circuitry to;

receive, at a first sensor system, track data from a second sensor system;

compare track data from the first sensor system to the track data from the second sensor system to determine if a track will be within a field of view of the first sensor system during a time period;

determine, at a first sensor system, predicted quality of tracks based on the track data from the first and second sensor systems;

broadcast the predicted quality of tracks;

receive predicted quality of tracks from the second sensor system; and

determine a first set of tasks based on the predicted quality of tracks determined by the first sensor system and the predicted quality of tracks received from the second sensor system.

17. The apparatus of claim 16 wherein the circuitry comprises at least one of a processor, a memory, programmable logic and logic gates.

18. The apparatus of claim 16, further comprising circuitry to:

receive, at the second sensor system, track data from a first sensor system;

compare track data from the second sensor system to the track data from the first sensor system to determine if a track will be within a field of view of the second sensor system during the time period;

receive predicted quality of tracks from the first sensor system; and

determine a second set of tasks based on the predicted quality of tracks determined by the second sensor system and the predicted quality of tracks received from the first sensor system.

19. The apparatus of claim 18 wherein the first set of tasks and the second set of task are substantially equivalent.

20. The apparatus of claim 16 wherein the circuitry to determine the first set of tasks comprises circuitry to determine a set of tasks performed by each sensor system.

21. The apparatus of claim 16 wherein circuitry to determine the first set of tasks comprises circuitry to determine a first set of tasks using a tabu algorithm.