Methods for two-dimensional autofocus in high resolution radar systems

• US 7,843,377 B2
• Filed: 02/12/2010
• Issued: 11/30/2010
• Est. Priority Date: 08/15/2006
• Status: Active Grant

• Current Assignee: Maxar Mission Solutions Incorporated (Galileo Parent, Inc.)
• Original Assignee: General Dynamics Advanced Information Systems Incorporated (General Dynamics Corporation)
• Inventors: Batteh, Elizabeth T., Goodman, Ron S., Gabl, Edward F., Ricoy, Mark A., Connell, Scott D.
• Primary Examiner(s): Tarcza; Thomas H
• Assistant Examiner(s): Bythrow; Peter M
• Application Number:
  US12/656,689
• Publication Number:
  US 20100149024A1
• Time in Patent Office: 291 Days
• Field of Search: 342/25.R, 342/25.A, 342/25.B, 342/25.C, 342/25.D, 342/25.E, 342/25.F, 342/175
• US Class Current: 342/25.00F
• CPC Class Codes: G01S 13/9011 with frequency domain processing of the SAR signals in azimuth G01S13/9005 takes precedence
• CPC Class Codes: G01S 13/9019 Auto-focussing of the SAR signals

Abstract

Provided are two-dimensional autofocus methods in a synthetic aperture radar (SAR) system which include: (1) two-dimensional pulse pair product algorithm including shear PGA, eigenvector phase history (“EPH”), shear PGA/EPH); (2) two-dimensional optimization algorithms including parametric one-dimensional estimate/two-dimensional correction, parametric two dimensional estimate/two-dimensional correction, unconstrained two-dimensional nonparametric and constrained two-dimensional nonparametric methods; (3) a two-dimensional geometry filter algorithm; (4) a two-dimensional prominent point processing algorithm; (5) a one-dimensional phase estimate of higher order two dimensional phase errors; and, (6) a fast SHARP parametric autofocus algorithm.

Claims

1. A two-dimensional polar geometry model method used in a synthetic aperture radar (SAR) system for removing a two-dimensional phase error in a complex image, the method comprising:

creating the complex image with a sensor;

modeling the two-dimensional phase error as a combination of a range error which is substantially identical from pulse to pulse and a slow-time error;

fitting an unconstrained two-dimensional estimate to the modeled two-dimensional phase error; and

correcting the two-dimensional phase error to generate a corrected image.

2. The method according to claim 1, wherein the modeling the two-dimensional phase error is solely based on azimuth or range.

3. The method according to claim 1, wherein the modeled two-dimensional phase error is represented as two one-dimensional vectors or two sets of parametric basic vectors.

4. The method according to claim 3, wherein a contrast metric is used to determine whether to use a model fit of original data which maximizes the contrast metric.

5. The method according to claim 4, wherein the contrast metric utilizes a line-power normalization of the complex image, a column-power normalization, or both.

6. A computer-readable medium having computer-executable instructions for a two-dimensional polar geometry filter method used in a synthetic aperture radar (SAR) system for removing a two-dimensional phase error in a complex image, the computer-executable instructions configured to perform a method comprising:

creating the complex image with a sensor;

modeling the two-dimensional phase error as a combination of a range error which is substantially identical from pulse to pulse and a slow-time error;

fitting an unconstrained two-dimensional estimate to the modeled two-dimensional phase error; and

correcting the two-dimensional phase error to generate a corrected image.

7. The computer-readable medium according to claim 6, wherein the modeling the two-dimensional phase error is solely based on azimuth or range.

8. The computer-readable medium according to claim 6, wherein the modeled two-dimensional phase error is represented as two one-dimensional vectors or two sets of parametric basic vectors.

9. The method according to claim 8, wherein a contrast metric is used to determine whether to use a model fit of the original data based on which maximizes the contrast metric.

10. The method according to claim 9, wherein the contrast metric utilizes a line-power normalization of the complex image, a column-power normalization, or both.