WIDE BEAM SAR FOCUSING METHOD USING NAVIGATION SOLUTION DERIVED FROM AUTOFOCUS DATA

• US 20150061927A1
• Filed: 06/28/2012
• Published: 03/05/2015
• Est. Priority Date: 01/10/2012
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Jin, Michael Yih-Hwa
• Granted Patent: US 9,239,383 B2
• Time in Patent Office: Days
• US Class Current: 342/25.F
• CPC Class Codes: G01S 13/90 using synthetic aperture techniques , e.g. synthetic aperture radar [SAR] techniques
• CPC Class Codes: G01S 13/9019 Auto-focussing of the SAR signals
• CPC Class Codes: G01S 13/904 SAR modes

Abstract

An algorithm for deriving improved navigation data from the autofocus results obtained from selected image blocks in a wide-beam synthetic aperture radar (SAR) image. In one embodiment the navigation error may be approximated with a vector of low-order polynomials, and a set of polynomial coefficients found which results in a good phase error match with the autofocus results. In another embodiment, a least squares solution may be found for the system of equations relating the phase errors at a point in time for selected image blocks to the navigation error vector at that point in time. An approach using low sample rate backprojection (150) initially to select suitable image blocks, and full sample rate backprojection (156) for the selected image blocks, followed by full sample rate backprojection (164) for the image, using the improved navigation solution, may be used to reduce the computational load of employing the algorithm.

Claims

1. A method for forming a synthetic aperture radar (SAR) image, from SAR data and a navigation profile, the method comprising:

generating a first SAR image from the SAR data and the navigation profile;

dividing the SAR image into image blocks;

selecting a subset of the image blocks;

applying an autofocus algorithm to each of the selected image blocks to form phase error profile estimates for the selected image blocks;

generating a navigation error profile estimate from the phase error profile estimates; and

generating a second SAR image from the SAR data, the navigation profile, and the navigation error profile estimate.

2. The method of claim 1, wherein the generating a navigation error profile estimate comprises:

approximating the navigation error profile estimate as a vector of three low-order polynomials in time and

searching the space of polynomial coefficient values for a set of values which optimizes a measure of performance for the navigation error profile estimate.

3. The method of claim 2, wherein the measure of performance is the weighted summed norm of the phase error, taken over a set of selected image blocks.

4. The method of claim 3, wherein an image block is selected on the basis of having image contrast exceeding a predetermined threshold.

5. The method of claim 3, wherein the weight, for a selected image block, used in calculating the weighted summed norm of the phase error, equals (i) the reciprocal of the square root of the image contrast before autofocus for that image block, multiplied by (ii) the ratio of (a) the image contrast before autofocus for that image block to (b) the image contrast after autofocus for that image block.

6. The method of claim 1, wherein the generating a navigation error profile estimate comprises:

selecting a set of image blocks; and

finding, for each point in time, the point in space which minimizes the weighted sum of the squares of the differences between the phase errors for the selected image blocks calculated from the navigation error profile, and the phase errors for the selected image blocks resulting from the autofocus algorithm.

7. The method of claim 6, wherein the selected image blocks are selected on the basis of having image contrast exceeding a predetermined threshold.

8. The method of claim 6, wherein the weight, for a selected image block, used in calculating the weighted sum, is a function of the image contrast before autofocus for that image block and the image contrast after autofocus for that image block.

9. The method of claim 6, wherein the weight, for a selected image block, used in calculating the weighted sum, equals (i) the reciprocal of the square root of the image contrast before autofocus for that image block, multiplied by (ii) the ratio of (a) the image contrast before autofocus for that image block to (b) the image contrast after autofocus for that image block.

10. The method of claim 1, wherein the generating a navigation error profile estimate comprises:

writing an intermediate navigation error profile estimate as a vector of three low-order polynomials in time;

searching the space of polynomial coefficient values for a set of values which optimizes a measure of performance for the intermediate navigation error profile estimate;

forming an intermediate navigation profile and an intermediate image block phase error profile using the set of values of the polynomial coefficients;

selecting a set of image blocks; and

using the intermediate navigation profile and the intermediate image block phase error profile to find, for each point in time, the point in space which minimizes the weighted sum of the squares of the differences between the phase errors for the selected image blocks calculated from the point in space, and the phase errors for the selected image blocks resulting from the autofocus algorithm.

11. A method for forming an improved navigation profile from a coarse navigation profile and from a synthetic aperture radar (SAR) image, the method comprising:

generating a first SAR image from the SAR data and the navigation profile;

dividing the SAR image into image blocks;

selecting a subset of the image blocks;

applying an autofocus algorithm to each of the selected image blocks to form phase error profile estimates for the selected image blocks; and

generating an improved navigation profile from the coarse navigation profile and the phase error profile estimates.

12. The method of claim 11, wherein the generating an improved navigation profile comprises:

approximating a navigation error profile estimate as a vector of three low-order polynomials in time;

searching the space of polynomial coefficient values for a set of values which optimizes a measure of performance for the navigation error profile estimate; and

correcting the coarse navigation profile using the navigation error profile estimate.

13. The method of claim 12, wherein the measure of performance is the weighted summed norm of the phase error, taken over a set of selected image blocks.

14. The method of claim 13, wherein an image block is selected on the basis of having image contrast exceeding a predetermined threshold.

15. The method of claim 13, wherein the weight, for a selected image block, used in calculating the weighted summed norm of the phase error, is a function of the image contrast before autofocus for that image block and the image contrast after autofocus for that image block.

16. The method of claim 13, wherein the weight, for a selected image block, used in calculating the weighted summed norm of the phase error, equals (i) the reciprocal of the square root of the image contrast before autofocus for that image block, multiplied by (ii) the ratio of (a) the image contrast before autofocus for that image block to (b) the image contrast after autofocus for that image block.

17. The method of claim 11, wherein the generating an improved navigation profile comprises:

selecting a set of image blocks; and

finding, for each point in time, the point in space which minimizes the weighted sum of the squares of the differences between the phase errors for the selected image blocks calculated from the point in space, and the phase errors for the selected image blocks resulting from the autofocus algorithm.

18. The method of claim 17, wherein an image block is selected on the basis of having image contrast exceeding a predetermined threshold.

19. The method of claim 17, wherein the weight for an image block in the weighted sum equals (i) the reciprocal of the square root of the image contrast before autofocus for that image block, multiplied by (ii) the ratio of (a) the image contrast before autofocus for that image block to (b) the image contrast after autofocus for that image block.

20. The method of claim 11, wherein the generating an improved navigation profile from the coarse navigation profile and the phase error profile estimates comprises:

approximating an intermediate navigation error profile estimate as a vector of three low-order polynomials in time;

searching the space of polynomial coefficient values for a set of values which optimizes a measure of performance for the intermediate navigation error profile estimate;

forming an intermediate navigation profile and an intermediate image block phase error profile using the set of values of the polynomial coefficients;

selecting a set of image blocks; and

using the intermediate navigation profile and the intermediate image block phase error profile to find, for each point in time, the point in space which minimizes the weighted sum of the squares of the differences between the phase errors for the selected image blocks calculated from the point in space, and the phase errors for the selected image blocks resulting from the autofocus algorithm.