Extended GLRT Detection of Moving Targets for Multichannel SAR Based on Generalized Steering Vector

Area of Science:

• Radar Signal Processing
• Synthetic Aperture Radar (SAR) Imaging
• Target Detection

Background:

• Traditional generalized likelihood ratio tests (GLRT) struggle with performance degradation in unfocused synthetic aperture radar (SAR) images.
• Multichannel SAR-ground moving-target indication (SAR-GMTI) systems are particularly affected by image defocus, impacting detection of low radar cross-section (RCS) and slow targets.

Purpose of the Study:

• To develop an extended GLRT detector robust to image defocus in SAR-GMTI systems.
• To enhance the detection and parameter estimation of moving targets, especially those with lower RCS and slower radial velocities.

Main Methods:

• Proposed an extended GLRT detector utilizing the generalized steering vector (GSV).
• Formulated a joint data vector from current and adjacent cells to derive the GSV.
• Evaluated performance using the optimum likelihood ratio test (LRT) under the Neyman-Pearson (NP) criterion.

Main Results:

• The extended GLRT effectively integrates signals coherently.
• Demonstrated improved moving-target detection and parameter estimation capabilities.
• Showcased robustness and effectiveness in simulated defocusing SAR images.

Conclusions:

• The proposed extended GLRT detector significantly overcomes the limitations of traditional methods in defocusing SAR images.
• This approach offers a more reliable solution for SAR-GMTI applications requiring accurate moving target detection.