RAPID ROBUST DETECTION DECREASER

• US 20190113624A1
• Filed: 10/16/2017
• Published: 04/18/2019
• Est. Priority Date: 10/16/2017
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Robinson, Ian S., Ploplys, Nicholas J.
• Granted Patent: US 10,788,583 B2
• Time in Patent Office: Days
• CPC Class Codes: G01S 13/72 for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
• 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 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 17/66 Tracking systems using electromagnetic waves other than radio waves
• CPC Class Codes: G01S 7/06 Cathode-ray tube displays or other two dimensional or three-dimensional displays
• CPC Class Codes: G01S 7/2922 by using a controlled threshold
• CPC Class Codes: G01S 7/51 Display arrangements

Abstract

A system for tracking targets. A sequence of sensor observations is processed with two thresholds, including a first threshold, and a second threshold, higher than the first threshold. Signals that exceed the first threshold are identified as low-confidence target detections and stored for possible future use. When a signal exceeds the higher second threshold, it is identified as a high-confidence detection, and one or more candidate tracks are formed, including the high-confidence detection and one or more low-confidence detections from within a neighborhood of the high-confidence detection.

Claims

1. A method for tracking targets by a system comprising one or more sensors configured to generate sensor observations and a processing circuit, the method comprising:

identifying, by the processing circuit, in each of a first sequence of sensor observations, a respective plurality of low-confidence target detections meeting a first threshold, each low-confidence target detection including a target position;

storing each of the pluralities of low-confidence target detections;

identifying, in a triggering sensor observation obtained after the first sequence of sensor observations, a high-confidence target detection meeting a second threshold, higher than the first threshold;

selecting a first subset of the plurality of low-confidence target detections in a neighborhood of the high confidence detection from a first sensor observation preceding the triggering sensor observation; and

forming a first target track, the first target track including the high-confidence target detection and a low-confidence target detection of the first subset.

2. The method of claim 1, further comprising iteratively, over a plurality of iterations beginning with a first iteration:

selecting, with each iteration, from a sensor observation associated with the iteration, a subset of the low-confidence target detections, the observation associated with the iteration preceding the sensor observation by an amount of time that increases with each iteration, the first subset being the subset selected in the first iteration;

updating a target track including the high-confidence target detection and one or more target detections from the subsets; and

calculating a quality metric for the target track,

until the quality metric exceeds a quality metric threshold.

3. The method of claim 1, further comprising displaying the first target track on a display.

4. The method of claim 1, wherein each low-confidence target detection further includes a target velocity.

5. The method of claim 1, wherein the first subset includes fewer than 0.1% of the low-confidence target detections from the first sensor observation.

6. The method of claim 1, wherein the first subset includes fewer than 1% of the low-confidence target detections from the first sensor observation.

7. The method of claim 1, wherein the neighborhood contains at most 10% of the low-confidence target detections of the first sensor observation.

8. The method of claim 1, wherein the neighborhood contains at most 1% of the low-confidence target detections of the first sensor observation.

9. The method of claim 8, wherein selecting a first subset of the plurality of low-confidence target detections further comprises selecting only low-confidence target detections meeting a third threshold, less than the first threshold and greater than the second threshold.

10. The method of claim 9, further comprising:

selecting a second subset of the plurality of low-confidence target detections from a second sensor observation preceding the first sensor observation,

forming an updated target track, the updated target track including;

the high-confidence target detection,

a low-confidence target detection of the first subset, and

a low-confidence target detection of the second subset.

11. The method of claim 10, wherein selecting a second subset of the plurality of low-confidence target detections comprises selecting only low-confidence target detections from within a neighborhood of the low-confidence target detection of the first subset.

12. The method of claim 10, wherein selecting a second subset of the plurality of low-confidence target detections further comprises selecting only low-confidence target detections meeting a fourth threshold, less than the first threshold and greater than the second threshold.

13. The method of claim 12, wherein the fourth threshold is less than the third threshold.

14. A system, comprising:

a sensor system comprising a first sensor, and being configured to generate a first sequence of sensor observations; and

a processing circuit, configured to;

identify, in each of the first sequence of sensor observations, a respective plurality of low-confidence target detections meeting a first threshold, each low-confidence target detection including a target position;

store each of the pluralities of low-confidence target detections;

identify, in a triggering sensor observation obtained after the first sequence of sensor observations, a high-confidence target detection meeting a second threshold, higher than the first threshold;

select a first subset of the plurality of low-confidence target detections in a neighborhood of the high confidence detection from a first sensor observation preceding the triggering sensor observation; and

form a first target track, the first target track including the high-confidence target detection and a low-confidence target detection of the first subset.

15. The system of claim 14,

wherein the sensor system further comprises a second sensor, different from the first sensor, and the sensor system is configured to generate the first sequence of sensor observations using:

data from the first sensor, and

data from the second sensor.

16. The system of claim 14, wherein the first sensor is an electro-optical sensor.

17. The system of claim 14, further comprising a display, and wherein the processing circuit is further configured to display the first target track on the display.

18. The method of claim 14, wherein each low-confidence target detection further includes a target velocity.