Adaptive Clutter Filter for Maritime Surface Search Radar

• US 20110102247A1
• Filed: 10/30/2009
• Published: 05/05/2011
• Est. Priority Date: 10/30/2009
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Applied Signal Technology Incorporated
• Inventors: Blind, Jason, Pauli, Mark D.
• Granted Patent: US 7,990,311 B2
• Time in Patent Office: Days
• US Class Current: 342/159
• CPC Class Codes: G01S 13/937 of marine craft
• CPC Class Codes: G01S 7/2927 by deriving and controlling a threshold value
• CPC Class Codes: G01S 7/414 Discriminating targets with respect to background clutter

Abstract

A time sequence of raw radar data for a region of space is subdivided into a plurality of processing frames. The processing frames are subdivided into a plurality of processing cells and iteratively processed by selecting a single processing cell for processing, transforming the radar data of the processing cell to form transformed radar data in either the time domain or the Fourier domain. The transformed data is converted to a Power Spectrum Density Matrix in the case of the Fourier domain and a Time Space Correlation Matrix in the case of the time domain. This is smoothed and thresholded and then the clutter for the processing cell is estimated. Estimated local non-speckle clutter is estimated and removed from the transformed radar data, with the cleaned transformed radar data converted back to the time domain if required.

Claims

1. A method, comprising:

obtaining a time sequence of raw radar data for a region of space;

subdividing the raw radar data into a plurality of processing frames;

for a processing frame, subdividing the processing frame into a plurality of processing cells and iteratively processing the processing cells of a processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

performing a Fourier transform to convert the transformed radar data from the time domain to the Fourier domain (FD) to form FD radar data;

converting the FD radar data to a FD Power Spectrum Density (FDPSD);

smoothing the FDPSD;

thresholding the FDPSD based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell;

removing the local non-speckle clutter from the processing cell in the Fourier domain to form filtered FD radar data; and

performing an inverse Fourier transform to convert the filtered FD radar data back to the time domain.

2. The method of claim 1, further comprising:

adjusting the threshold parameter.

3. The method of claim 1, further comprising:

combining a plurality of processed processing cells into a processed processing frame.

4. The method of claim 3, further comprising:

combining a plurality of processed processing frames into a time sequence of filtered radar data.

5. The method of claim 1, further comprising:

using a windowing technique in the removing step.

6. The method of claim 5, wherein the windowing technique is the Overlap-Save Method.

7. The method of claim 1, wherein the transforming step includes taking a natural logarithm of the radar data.

8. The method of claim 1, wherein the processing frames are divided among more than one processor for processing.

9. An apparatus, comprising:

means for obtaining a time sequence of raw radar data for a region of space;

means for subdividing the raw radar data into a plurality of processing frames;

means for subdividing the processing frame into a plurality of processing cells and iteratively processing the processing cells of a processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

performing a Fourier transform to convert the transformed radar data from the time domain to the Fourier domain (FD) to form FD radar data;

converting the FD radar data to a FD Power Spectrum Density (FDPSD);

smoothing the FDPSD;

thresholding the FDPSD based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell;

removing the local non-speckle clutter from the processing cell in the Fourier domain to form filtered FD radar data; and

performing an inverse Fourier transform to convert the filtered FD radar data back to the time domain.

10. The apparatus of claim 9, further comprising:

means for adjusting the threshold parameter.

11. The apparatus of claim 10, wherein the means for adjusting the threshold parameter is configured to be operated by an operator.

12. The apparatus of claim 9, further comprising:

means for combining a plurality of processed processing cells into a processed processing frame.

13. The apparatus of claim 12, further comprising:

means for combining a plurality of processed processing frames into a time sequence of filtered radar data.

14. The apparatus of claim 9, wherein a windowing technique is used in the removing.

15. The apparatus of claim 14, wherein the windowing technique is the Overlap-Save Method.

16. The apparatus of claim 9, wherein the transforming includes taking a natural logarithm of the radar data.

17. The apparatus of claim 9, wherein the means for processing a frame include a plurality of individual processors operating in parallel to individually process frames.

18. An apparatus, comprising:

an input device configured to receive a time sequence of raw radar data for a region of space;

a processing device configured to subdivide the raw radar data into a plurality of processing frames;

a processing device configured subdivide a processing frame into a plurality of processing cells and iteratively process the processing cells of the processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

performing a Fourier transform to convert the transformed radar data from the time domain to the Fourier domain (FD) to form FD radar data;

converting the FD radar data to a FD Power Spectrum Density (FDPSD);

smoothing the FDPSD;

thresholding the FDPSD based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell;

removing the local non-speckle clutter from the processing cell in the Fourier domain to form filtered FD radar data; and

performing an inverse Fourier transform to convert the filtered FD radar data back to the time domain.

19. A method, comprising:

obtaining a time sequence of raw radar data for a region of space;

subdividing the raw radar data into a plurality of processing frames;

for a processing frame, subdividing the processing frame into a plurality of processing cells and iteratively processing the processing cells of a processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

converting the transformed radar data to a Time Space Correlation Matrix (TSCM);

smoothing the TSCM;

thresholding the TSCM based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell;

removing the local non-speckle clutter from the processing cell to form filtered radar data.

20. The method of claim 19, further comprising:

adjusting the threshold parameter.

21. The method of claim 19, further comprising:

combining a plurality of processed processing cells into a processed processing frame.

22. The method of claim 21, further comprising:

combining a plurality of processed processing frames into a time sequence of cleaned radar data.

23. The method of claim 19, wherein the transforming the radar data includes taking a natural logarithm of the radar data.

24. The method of claim 19, wherein the processing frames are divided among more than one processor for processing.

25. An apparatus, comprising:

means for obtaining a time sequence of raw radar data for a region of space;

means for subdividing the raw radar data into a plurality of processing frames;

means for subdividing the processing frame into a plurality of processing cells and iteratively processing the processing cells of a processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

converting the transformed radar data to a Time Space Correlation Matrix (TSCM);

smoothing the TSCM;

thresholding the TSCM based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell;

removing the local non-speckle clutter from the processing cell to form filtered radar data.

26. The apparatus of claim 25, further comprising:

means for adjusting the threshold parameter.

27. The apparatus of claim 26, wherein the means for adjusting the threshold parameter is configured to be operated by an operator.

28. The apparatus of claim 25, further comprising:

means for combining a plurality of processed processing cells into a processed processing frame.

29. The apparatus of claim 28, further comprising:

means for combining a plurality of processed processing frames into a time sequence of cleaned radar data.

30. The apparatus of claim 25, wherein the transforming the radar data includes taking a natural logarithm of the radar data.

31. The apparatus of claim 25, wherein the means for processing a frame include a plurality of individual processors operating in parallel to individually process frames.

32. An apparatus, comprising:

an input device configured to receive a time sequence of raw radar data for a region of space;

a processing device configured to

subdivide the raw radar data into a plurality of processing frames;

subdivide a processing frame into a plurality of processing cells; and

iteratively process the processing cells of the processing frame by

selecting a single processing cell for processing;

transforming the radar data of the processing cell to form transformed radar data;

converting the transformed radar data to a Time Space Correlation Matrix (TSCM);

smoothing the TSCM;

thresholding the TSCM based upon a threshold parameter;

estimating the speckle clutter noise power for the processing cell;

estimating the local non-speckle clutter for the processing cell; and

removing the local non-speckle clutter from the processing cell to form filtered radar data.