Target detection in a SAR-imaged sea area

• US 8,665,131 B2
• Filed: 05/29/2008
• Issued: 03/04/2014
• Est. Priority Date: 05/29/2008
• Status: Active Grant

• Current Assignee: Telespazio SPA (Leonardo S.p.A.)
• Original Assignee: Telespazio SPA (Leonardo S.p.A.)
• Inventors: Eusebi Borzelli, Gian Luca, Ioannone, Alissa, Costantini, Mario
• Primary Examiner(s): Brainard, Timothy A
• Application Number:
  US12/994,538
• Publication Number:
  US 20110169686A1
• Time in Patent Office: 2,105 Days
• Field of Search: 342/25.R
• US Class Current: 342/25.R
• CPC Class Codes: G01S 13/9027 Pattern recognition for feature extraction
• CPC Class Codes: G01S 7/414 Discriminating targets with respect to background clutter

Abstract

Disclosed herein is a method of detecting a target in a sea area based on a Synthetic Aperture Radar (SAR) image thereof. The Synthetic Aperture Radar (SAR) image is made up of pixels, each having a respective magnitude. The method comprises computing a first reference quantity which characterizes a Poisson distribution assumed for the magnitudes that the pixels in the Synthetic Aperture Radar (SAR) image would have if the sea area were free of targets. The method further comprises selecting pixels in the Synthetic Aperture Radar (SAR) image, computing a real quantity which characterizes a real statistical distribution of the magnitudes of the selected pixels, and detecting a target in the sea area based on the computed first reference and real quantities. The selected pixels are in a one and the same sub-image of the Synthetic Aperture Radar (SAR) image, and detecting comprises detecting a target in a sea subarea of the sea area, the sea subarea being represented by the sub-image.

Claims

1. Method of detecting a target in a sea area based on a Synthetic Aperture Radar (SAR) image thereof, the Synthetic Aperture Radar (SAR) image made up of pixels, each having a respective magnitude, the method comprising:

using an electronic processor to compute a first reference quantity characterizing a Poisson distribution assumed for the magnitudes that the pixels in the Synthetic Aperture Radar (SAR) image would have if the sea area were free of targets;

selecting pixels in the Synthetic Aperture Radar (SAR) image;

computing a real quantity characterizing a real statistical distribution of the magnitudes of the selected pixels; and

detecting a target in the sea area based on the computed first reference and real quantities.

2. The method of claim 1, wherein the selected pixels are in a one and the same sub-image of the Synthetic Aperture Radar (SAR) image, and detecting comprises detecting a target in a sea subarea of the sea area, the sea subarea being represented by the sub-image.

3. The method of claim 1, wherein the first reference quantity is indicative of a mean value of the magnitudes of the pixels in the Synthetic Aperture Radar (SAR) image.

4. The method of claim 1, wherein computing a first reference quantity (block 14) is based on some Synthetic Aperture Radar (SAR) images of the sea area, each representing the sea area at a respective time.

5. The method of claim 4, wherein the first reference quantity is indicative of a mean value of the magnitudes of the pixels in said some Synthetic Aperture Radar (SAR) images.

6. The method of claim 1, wherein the Poisson distribution is characterized by an expected value based on the first reference quantity.

7. The method of claim 1, wherein the Poisson distribution is characterized by an expected value equal to the first reference quantity.

8. The method of claim 1, wherein computing a real quantity (block 15) comprises computing a histogram of the magnitudes of the selected pixels, and providing the real quantity based on the histogram.

9. The method of claim 1, wherein detecting comprises:

comparing the real quantity with a second reference quantity, the real quantity and the second reference quantity being indicative of a one and the same characteristic value of, respectively, the real statistical distribution and the Poisson distribution; and

detecting a target based on comparing.

10. The method of claim 9, wherein the characteristic value is the most frequently occurring magnitude.

11. The method of claim 9, wherein detecting a target based on comparing comprises detecting a target when comparing satisfies a given condition.

12. The method of claim 11, wherein said given condition is defined by the fact that a difference between the second reference and real quantities is greater than a detection threshold.

13. The method of claim 12, wherein the detection threshold is based on the Poisson distribution.

14. The method of claim 12, wherein the detection threshold is based on the standard deviation of the Poisson distribution.

15. The method of claim 12, wherein the detection threshold is equal to a fraction of the standard deviation of the Poisson distribution.

16. The method of claim 12, wherein the detection threshold is equal to a third of the standard deviation of the Poisson distribution.

17. The method of claim 12, further comprising:

computing a third reference quantity which is indicative of a mean value of the magnitudes of the pixels in some Synthetic Aperture Radar (SAR) images of the sea area, each Synthetic Aperture Radar (SAR) image representing the sea area at a respective time; and

characterizing a second Poisson distribution by basing the corresponding expected value on the third reference quantity; and

wherein the detection threshold is based on the second Poisson distribution.

18. The method of claim 17, wherein the second Poisson distribution is characterized by an expected value equal to the third reference quantity.

19. The method of claim 17, wherein the detection threshold is based on the standard deviation of the second Poisson distribution.

20. The method of claim 17, wherein the detection threshold is equal to a fraction of the standard deviation of the second Poisson distribution.

21. The method of claim 17, wherein the detection threshold is equal to a third of the standard deviation of the second Poisson distribution.

22. An electronic system for detecting a target in a sea area based on a Synthetic Aperture Radar (SAR) image thereof, the Synthetic Aperture Radar (SAR) image made up of pixels, each having a respective magnitude, the electronic system comprising:

an electronic processor coupled to a Synthetic Aperture Radar (SAR) system to acquire data therefrom, and

a software program comprising software code portions which, when the software program is run on the electronic processor, configures the electronic system to;

compute a first reference quantity characterizing a Poisson distribution assumed for the magnitudes that the pixels in the Synthetic Aperture Radar (SAR) image would have if the sea area were free of targets;

select pixels in the Synthetic Aperture Radar (SAR) image;

compute a real quantity characterizing a real statistical distribution of the magnitudes of the selected pixels; and

detect a target in the sea area based on the computed first reference and real quantities.

23. An electronic device for detecting a target in a sea area based on a Synthetic Aperture Radar (SAR) image thereof, the Synthetic Aperture Radar (SAR) image made up of pixels, each having a respective magnitude, the electronic device being configured to:

compute a first reference quantity characterizing a Poisson distribution assumed for the magnitudes that the pixels in the Synthetic Aperture Radar (SAR) image would have if the sea area were free of targets;

select pixels in the Synthetic Aperture Radar (SAR) image;

compute a real quantity characterizing a real statistical distribution of the magnitudes of the selected pixels; and

detect a target in the sea area based on the computed first reference and real quantities.