Synthetic aperture radar motion estimation method

• US 7,646,327 B1
• Filed: 07/30/2008
• Issued: 01/12/2010
• Est. Priority Date: 07/30/2008
• Status: Expired due to Fees

• Current Assignee: the united states of america as represented by the secretary of the navy
• Original Assignee: the united states of america as represented by the secretary of the navy
• Inventors: Roth, Duane, Freeman, Will
• Primary Examiner(s): Sotomayor; John B
• Application Number:
  US12/182,910
• Time in Patent Office: 531 Days
• Field of Search: 342/25.R, 342 25 A- 25 F, 342159-162, 342/192, 342194-196
• US Class Current: 342/25.00B
• CPC Class Codes: G01S 13/9019 Auto-focussing of the SAR signals
• CPC Class Codes: G01S 13/9029 specially adapted for moving target detection within a single SAR image or within multiple SAR images taken at the same time

Abstract

A target object motion estimation method using at least one subset of a complex SAR image. Coarse range cell alignment is performed on at least one subset of a complex SAR image. At least one subset is autofocused, thereby providing an estimated phase error function. The estimated phase error function yielded by autofocusing (or a manipulated version of the phase error function) may be analyzed to detect, characterize, and estimate target object motion.

Claims

1. A method for detecting motion comprising:

providing an original complex SAR image, the SAR image having a target object;

defining a regional subset of the original complex SAR image;

performing coarse range cell alignment on said regional subset;

autofocusing said regional subset to produce an estimated phase error function;

analyzing the amplitude and frequency of said generated estimated phase error function;

detecting motion of said target object based on said analysis.

2. The method of claim 1 further comprising the steps of:

removing linear bias present in said estimated phase error function to provide an unbiased estimated phase error function;

analyzing the amplitude and frequency of said unbiased estimated phase error function; and

detecting motion of said target object based on said analysis.

3. The method of claim 1 further comprising the steps of:

filtering said estimated phase error function to remove slow variations and low frequency components to produce a filtered estimated phase error function;

analyzing the amplitude and frequency of said filtered estimated phase error function;

and

detecting motion of said target object based on said analysis.

4. The method of claim 1 further comprising the steps of:

pseudo unwrapping said estimated phase error function to yield a pseudo unwrapped estimated phase error function;

analyzing the amplitude and frequency of said pseudo unwrapped estimated phase error function; and

detecting motion of said target object based on said analysis.

5. The method of claim 1 further comprising the steps of:

removing linear bias present in said estimated phase error function to provide an unbiased estimated phase error function;

filtering said unbiased estimated phase error function to remove slow variations and low frequency components from said unbiased estimated phase error function to produce a filtered unbiased estimated phase error function;

analyzing the amplitude and frequency of said filtered unbiased estimated phase error function; and

detecting motion of said target object based on said analysis.

6. The method of claim 1 further comprising the steps of:

removing linear bias present in said estimated phase error function to provide an unbiased estimated phase error function;

pseudo unwrapping said unbiased estimated phase error function to yield a pseudo unwrapped unbiased estimated phase error function;

analyzing the amplitude and frequency of said pseudo unwrapped unbiased estimated phase error function; and

detecting motion of said target object based on said analysis.

7. The method of claim 1 further comprising the steps of:

removing linear bias present in said estimated phase error function to provide an unbiased estimated phase error function;

filtering said unbiased estimated phase error function to remove slow variations and low frequency components from said unbiased estimated phase error function to produce a filtered unbiased estimated phase error function;

pseudo unwrapping said filtered unbiased estimated phase error function to yield a pseudo unwrapped filtered unbiased estimated phase error function;

analyzing the amplitude and frequency of said pseudo unwrapped filtered unbiased estimated phase error function; and

detecting motion of said target object based on said analysis.

8. The method of claim 1 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

9. The method of claim 2 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

10. The method of claim 3 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

11. The method of claim 4 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

12. The method of claim 5 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

13. The method of claim 6 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

14. The method of claim 7 further comprising the step of:

Estimating fine displacement motion by solving for d in the equation φ

=2π

d/λ

_c, where φ

is the estimated phase error.

15. The method of claim 1 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the estimated phase error function.

16. The method of claim 2 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the unbiased estimated phase error function.

17. The method of claim 3 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the filtered estimated phase error function.

18. The method of claim 4 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the pseudo unwrapped estimated phase error function.

19. The method of claim 6 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the pseudo unwrapped unbiased estimated phase error function.

20. The method of claim 7 further comprising the step of:

Characterizing fine displacement motion of the target object based on the amplitude and frequency of the pseudo unwrapped filtered unbiased estimated phase error function.