Knowledge aided detector

Patent metadata

Field	Value
Publication number	US-9157992-B2
Application number	US-201213674563-A
Country	US
Kind code	B2
Filing date	Nov 12, 2012
Priority date	Feb 2, 2012
Publication date	Oct 13, 2015
Grant date	Oct 13, 2015

Abstract

Various embodiments are described herein for a detector and method that perform various types of CFAR detection on radar data including knowledge-aided CFAR detection, hybrid-CFAR detection and simplified censored CFAR detection. Knowledge about the type of local environment of a Cell Under Test and the proximity of the Cell Under Test to various types of noise can be used to select particular types of CFAR detection methods or combinations thereof. In other instances, certain parameters of a CFAR detection method can be adapted based on this knowledge.

First claim

The invention claimed is:

1. A method of performing target detection in a radar system on a Cell Under Test (CUT) associated with a reference window of range-Doppler radar values, wherein the method comprises:
by a detector of the radar system:
determining if a local noise environment of the CUT is homogeneous or non-homogenous; and
picking a size of the reference window based on whether the local noise environment is homogeneous or non-homogeneous;
ordering the range-Doppler radar values in the reference window to produce ordered range-Doppler radar values;
obtaining an average value of a percentage of the ordered range-Doppler radar values based on a percentage threshold;
multiplying the average value by a threshold coefficient to obtain a first threshold value; and
detecting a target if a radar value associated with the CUT is larger than the first threshold value.

2. The method of claim 1 , wherein determining whether the local noise environment is homogeneous or non-homogeneous comprises:
determining a statistic of the range-Doppler values in a second reference window containing the CUT; and
comparing the statistic with a predefined noise threshold,
wherein the statistic comprises one of a variance and a standard deviation.

3. The method of claim 1 , wherein the method further comprises orienting the reference window along the Doppler dimension if the CUT is determined to he in or near an ionospheric clutter region.

4. The method of claim 1 , wherein the method further comprises orienting the reference window along the range dimension if the CUT is near a Bragg line and is not in an ionospheric clutter region or is not near the ionospheric clutter region.

5. The method of claim 1 , wherein the method further comprises determining the threshold coefficient based on a size of the reference window and a detection probability.

6. The method of claim 1 , wherein the method further comprises increasing the percentage threshold in signal rich environments and decreasing the percentage threshold in sparse signal environments.

7. A method of performing target detection in a radar system on a Cell Under Test (CUT) associated with a reference window of range-Doppler radar values, wherein the method comprises:
by a detector of the radar system:
obtaining a first threshold value according to a first different CFAR detection method comprising the steps of:
ordering the range-Doppler radar values in the reference window to produce ordered range-Doppler radar values;
obtaining an average value of a percentage of the ordered range-Doppler radar values based on a percentage threshold; and
multiplying the average value by a threshold coefficient to obtain the first threshold value;

obtaining a second threshold value according to a second different CFAR detection method;
setting a third threshold value to the larger of the first and second threshold values; and
detecting a target if a radar value associated with the CUT is larger than the third threshold.

8. The method of claim 7 , wherein the second CFAR detection method comprises one of an Order-Statistics CFAR detection method, a Smallest-Of CFAR detection method, a Cell-Averaging CFAR detection method, a Greatest Of (GO)-CFAR detection method and a Trimmed Mean (TM)-CFAR detection method.

9. The method of claim 7 , wherein prior to the ordering step the method further comprises:
determining if a local noise environment of the CUT is homogeneous or non-homogeneous; and
picking a size of the reference window based on whether the local noise environment is homogeneous or non-homogenous.

10. The method of claim 9 , wherein determining whether the local noise environment is homogeneous or non-homogeneous comprises:
determining a statistic of the range-Doppler values in a second reference window containing the CUT; and
comparing the statistic with a predefined noise threshold,
wherein the statistic comprises one of a variance and a standard deviation.

11. The method of claim 9 , wherein the method further comprises orienting the reference window along the Doppler dimension if the CUT is determined to be in or near an ionospheric clutter region.

12. The method of claim 9 , wherein the method further comprises orienting the reference window along the range dimension if the CUT is near a Bragg line and is not in an ionospheric clutter region or is not near the ionospheric clutter region.

13. The method of claim 7 , wherein the method further comprises determining the threshold coefficient based on a size of the reference window and a detection probability.

14. The method of claim 7 , wherein the method further comprises increasing the percentage threshold in signal rich environments and decreasing the percentage threshold in sparse signal environments.

15. A method of performing target detection in a radar system on a Cell Under Test (CUT) associated with a plurality of range-Doppler radar values, wherein the method comprises, by a detector of the radar system:
classifying a local noise environment of the CUT using a first reference window;
selecting a size and a shape of a second reference window based on the classified local noise environment of the CUT;
selecting a type of Constant False Alarm Rate (CFAR) detection method and an orientation of the second reference window depending on a location of the CUT in relation to at least one of an ionospheric clutter region and a Bragg line; and
applying the selected CFAR detection method to detect a target at the CUT in the second reference window.

16. The method of claim 15 , wherein if the CUT is in dose proximity to the ionospheric clutter region, the method further comprises determining a shift factor and shifting the second reference window by the shift factor away from the ionospheric clutter region.

17. The method of claim 16 , wherein if the CUT is in close proximity to a Bragg line, the method further comprises selecting the type of CFAR detection method to be a combination of a Smallest-Of CFAR detection method and a simplified censored Cell-Averaging (CA)-CFAR detection method and orienting the second reference window along a Doppler dimension.

18. The method of claim 16 , wherein if the CUT is not in close proximity to a Bragg line, the method further comprises selecting the type of CFAR detection method to be a combination of an Order Statistics (OS)-CFAR detection method and a simplified censored Cell-Averaging (CA)-CFAR detection method and orienting the second reference window along a Doppler dimension.

19. The method of claim 15 , wherein if the CUT is not in close proximity to the ionospheric clutter region, the method further comprises selecting the type of CFAR detection method to be a combination of an Order-Statistics CFAR detection method and a simplified censored Cell-Averaging (CA)-CFAR detection method and orienting the second reference window along a range dimension.

20. The method of claim 15 , wherein if the CUT is within the ionospheric clutter region, the method further comprises selecting the type of CFAR detection method to be a combination of an Order-Statistics (OS)-CFAR detection method and a simplified censored Cell-Averaging (CA)-CFAR detection method, increasing a threshold parameter used in the OS-CFAR detection method and orienting the second reference window along a Doppler dimension.

21. The method of claim 15 , wherein the method further comprises determining if the location of the CUT is near the ionospheric clutter region, within the ionosphe

Assignees

• Raytheon Canada Ltd

Inventors

• Wang Jian
• Ponsford Anthony M
• Wang Emily

Classifications

• G01S7/2922

  by using a controlled threshold · CPC title

• G01S13/04 Primary

  Systems determining presence of a target (based on relative movement of target G01S13/56) · CPC title

• G01S2013/0227

  OTH, Over-The-Horizon radar · CPC title

• G01S13/5246

  post processors for coherent MTI discriminators, e.g. residue cancellers, CFAR after Doppler filters · CPC title

• G01S13/5244

  Adaptive clutter cancellation (specially adapted for airborne MTI, G01S13/5242) · CPC title