System and method for auto calibrated reduced rank adaptive processor

• US 6,801,161 B2
• Filed: 12/05/2002
• Issued: 10/05/2004
• Est. Priority Date: 12/05/2001
• Status: Active Grant

• Current Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Original Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Inventors: Divine, Dwight III, Lehtomaki, Norman A., Baker, Gregory A.
• Primary Examiner(s): Tarcza, Thomas H.
• Assistant Examiner(s): MULL, FRED H
• Application Number:
  US10/310,158
• Publication Number:
  US 20030122710A1
• Time in Patent Office: 670 Days
• Field of Search: 342/377-383
• US Class Current: 342/377
• CPC Class Codes: G01S 13/5244 Adaptive clutter cancellation specially adapted for airborne MTI, G01S13/5242
• CPC Class Codes: G01S 3/72 Diversity systems specially adapted for direction-finding
• CPC Class Codes: G01S 3/74 Multi-channel systems specially adapted for direction-finding, i.e. having a single antenna system capable of giving simultaneous indications of the directions of different signals systems in which the directions of different signals are determined sequentially and displayed simultaneously G01S3/04, G01S3/14
• CPC Class Codes: G01S 7/2813 Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays specially adapted to secondary radar systems G01S13/762; aerials or aerials systems H01Q21/29, H01Q25/00
• CPC Class Codes: G01S 7/4017 of HF systems

Abstract

The present invention describes a space-time adaptive processing (STAP) system and method combining adaptive processing with automatic phase calibration providing an improved signal-to-noise ratio of a received signal. The adaptive processing is accomplished by calculating a reduced rank approximation of a factorization of a covariance matrix via a partial singular value decomposition of the data matrix. According to the present invention, the calculation of a white noise gain constraint does not require knowledge or estimation of the noise floor. Automatic phase calibration using the signal data as the calibration source combined with the adaptive processing according to the present invention provides and enhance signal-to-noise ratio and clutter suppression.

Claims

1. A signal processing system for adaptively processing signals received by an antenna array and organized into a data matrix that enhances the signal-to-noise ratio of the signals, comprising:

an antenna array, and

a signal processor connected to the antenna array including a phase calibration element for correcting phase errors in the received signals using the received signals as a calibration source by locating a delay bin of a direct blast and time aligning the received signals, and an adaptive processing element for calculating adaptive weights from a reduced rank approximation of a factorization of a covariance matrix calculated from a partial singular value decomposition of the data matrix.

2. The system of claim 1, wherein the signal processor further comprises a preprocessing element to down convert the received signals to baseband and match filter the received signals.

3. The system of claim 1, wherein the signal processor further comprises one or more analog to digital converters for converting the signals received by the array antenna.

4. The system of claim 1, wherein the signal processor further comprises multipliers for applying the adaptive weights to the signals.

5. The system of claim 1, wherein the signal processor further comprises a summation element for combining the adaptively weighted signals into a single signal representing the received signals.

6. A method for processing signals received by an antenna array for improving the signal-to-noise ratio of the received signals, comprising the steps of:

automatically calibrating the phase of the received signals to correct for phase errors in the antenna array by locating a delay bin of a direct blast and time aligning the received signals; and

adaptively processing the signals.

7. The method of claim 6, wherein the step of automatically calibrating the phase of the received signals further comprises the steps of:

computing differential phase across the array for each pulse; and

median filtering across the pulses to eliminate outlying signals.

8. The method of claim 7, wherein the step of automatically calibrating the phase of the received signals further comprises the steps of:

computing an average differential phase for the received signals;

subtracting the average differential phase across the received signals to create a resulting phase representing phase errors; and

integrating the resulting phase across the received signals to produce phase corrected signals.

9. The method of claim 6, wherein the step of automatically calibrating the phase of the received signals further comprises the step of using the received signals as the calibration source.

10. The method of claim 6, wherein the step of adaptively processing the received signals further comprises the step of transforming the received signals to beamspace.

11. The method of claim 10, wherein the step of adaptively processing the received signals further comprises the step of transforming the received signals to Doppler space.

12. The method of claim 6, wherein the step of adaptively processing the received signals further comprises the step of calculating a steering vector over the array for a specified number of pulses.

13. The method of claim 12, wherein the step of adaptively processing the received signals further comprises the step of calculating a reduced rank approximation of a factorization of the covariance matrix via a partial singular value decomposition of a data matrix.

14. The method of claim 13, wherein the step of adaptively processing the received signals further comprises the steps of:

partitioning the dominant eigenvalues from the covariance matrix;

incorporating the dominant eigenvalues of the covariance matrix;

calculating a beam dependent white noise gain constraint;

calculating the adaptive weights by using the dominant eigenvalues;

applying the adaptive weights to the received signals; and

summing the weighted signals.

15. The method of claim 13, wherein the step of adaptively processing the received signals further comprises the steps of:

partitioning the singular values of the data matrix;

calculating a beam dependent white noise gain constraint;

calculating the adaptive weights by using the singular values

applying the adaptive weights to the received signals; and

summing the weighted signals.

16. The method of claim 6, further comprising the step of preprocessing the received signals.

17. The method of claim 16, wherein the step of preprocessing the received signals comprises the steps of:

down converting the received signals to baseband; and

match filtering the converted received signals.

18. The method of claim 6, further comprising the step of creating a data matrix from snapshots of the received signals over time.

19. The method of claim 6, wherein the step of adaptively processing the received signals further comprises the step of calculating adaptive weights without calculating a noise floor.