System and method for denoising synthetic aperture radar (SAR) images via sparse and low-rank (SLR) decomposition and using SAR images to image a complex scene

Patent metadata

Field	Value
Publication number	US-10310074-B1
Application number	US-201514670199-A
Country	US
Kind code	B1
Filing date	Mar 26, 2015
Priority date	Mar 27, 2014
Publication date	Jun 4, 2019
Grant date	Jun 4, 2019

Abstract

Described is a system for synthetic aperture radar (SAR) imaging. The system is adapted to reconstruct a set of images to generate a set of reconstructed SAR images, wherein at least some of the reconstructed SIR images have noise and contain glint. The reconstructed SAR images are then stacked into a matrix D, in which each column of the matrix is a reconstructed SAR image. Using sparse and low-rank decomposition on the matrix D, the system then extracts a clean background from the reconstructed SAR images and separates the noise and glint. Based on that, the system is operable to detect moving targets in sparse part S and issuing a notification of such a moving target.

First claim

What is claimed is:

1. A system for synthetic aperture radar (SAR) imaging, the system comprising:
a SAR attached with a moving platform;
one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of:
capturing a set of images with the SAR from different azimuth angles;
generating a set of reconstructed SAR images by reconstructing the set of images, wherein at least some of the reconstructed SAR images have noise and contain glint;
stacking the reconstructed SAR images into a matrix D, in which each column of the matrix is a reconstructed SAR image; and
generating a denoised SAR image by decomposing matrix D to extract a clean background from the reconstructed SAR images and separate the noise and glint from the reconstructed SAR images as sparse part S, the clean background being the denoised SAR image.

2. The system as set forth in claim 1 , further comprising instructions encoded on the non-transitory computer-readable medium for causing the one or more processors to perform an operation of detecting moving targets in sparse part S and issuing a notification of such a moving target.

3. The system as set forth in claim 2 , wherein detecting moving targets in sparse part S is performed using a segmentation method selected from a group consisting of normalized cut and active contour segmentation.

4. The system as set forth in claim 3 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

5. The system as set forth in claim 4 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

6. The system as set forth in claim 1 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

7. The system as set forth in claim 1 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

8. A computer implemented method using one or more processors for synthetic aperture radar (SAR) imaging, the method comprising acts of:
capturing a set of images with a SAR from different azimuth angles;
generating a set of reconstructed SAR images by reconstructing the set of images, wherein at least some of the reconstructed SAR images have noise and contain glint;
stacking the reconstructed SAR images into a matrix D, in which each column of the matrix is a reconstructed SAR image; and
generating a denoised SAR image by decomposing matrix D to extract a clean background from the reconstructed SAR images and separate the noise and glint from the reconstructed SAR images as sparse part S, the clean background being the denoised SAR image.

9. The computer implemented method as set forth in claim 8 , further comprising an act of detecting moving targets in sparse part S and issuing a notification of such a moving target.

10. The computer implemented method as set forth in claim 9 , wherein detecting moving targets in sparse part S is performed using a segmentation method selected from a group consisting of normalized cut and active contour segmentation.

11. The computer implemented method as set forth in claim 10 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

12. The computer implemented method as set forth in claim 11 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

13. The computer implemented method as set forth in claim 8 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

14. The computer implemented method as set forth in claim 8 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

15. A computer program product for synthetic aperture radar (SAR) imaging, the computer program product comprising:
a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of:
capturing a set of images with a SAR from different azimuth angles;
generating a set of reconstructed SAR images by reconstructing the set of images, wherein at least some of the reconstructed SAR images have noise and contain glint;
stacking the reconstructed SAR images into a matrix D, in which each column of the matrix is a reconstructed SAR image; and
generating a denoised SAR image by decomposing matrix D to extract a clean background from the reconstructed SAR images and separate the noise and glint from the reconstructed SAR images as sparse part S, the clean background being the denoised SAR image.

16. The computer program product as set forth in claim 15 , further comprising instructions encoded on the non-transitory computer-readable medium for causing the one or more processors to perform an operation of detecting moving targets in sparse part S and issuing a notification of such a moving target.

17. The computer program product as set forth in claim 16 , wherein detecting moving targets in sparse part S is performed using a segmentation method selected from a group consisting of normalized cut and active contour segmentation.

18. The computer program product as set forth in claim 17 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

19. The computer program product as set forth in claim 18 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

20. The computer program product as set forth in claim 15 , wherein in reconstructing the set of images, each image is constructed for a different set of azimuth angles.

21. The computer program product as set forth in claim 15 , wherein the set of reconstructed SAR images are reconstructed using a filtered back projection method.

Assignees

• Hrl Lab Llc

Inventors

• Ni Kang-Yu
• Rao Shankar R

Classifications

• G06T12/20

  Inverse problem, i.e. transformations from projection space into object space · CPC title

• G06T2207/10044

  Radar image · CPC title

• G06T7/194

  involving foreground-background segmentation · CPC title

• G01S13/9017

  with time domain processing of the SAR signals in azimuth (G01S13/9005 takes precedence) · CPC title

• G06T7/20

  Analysis of motion (motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51) · CPC title