A Novel Detection Scheme in Image Domain for Multichannel Circular SAR Ground-Moving-Target Indication

Area of Science:

• Radar Systems Engineering
• Signal Processing
• Remote Sensing

Background:

• Circular synthetic aperture radar (CSAR) enables long-duration, multi-angle observations, ideal for moving-target detection (MTD).
• Traditional MTD methods struggle with high probabilities of false alarm (PFA) due to strong clutter interference.

Purpose of the Study:

• To develop a robust MTD scheme for CSAR data that effectively suppresses strong clutter and minimizes false alarms.
• To enhance the detection of slow and weakly moving targets in challenging clutter environments.

Main Methods:

• A three-step scheme involving clutter background extraction, multichannel clutter suppression, and a novel degree of linear consistency of radial velocity interferometric phase (DLRVP) test.
• Clutter mask extraction using spatial similarity and sub-aperture image correlation.
• Amplitude-based detection and DLRVP test for enhanced PFA reduction.

Main Results:

• The proposed method achieved a PFA that is only 20% of the comparison method.
• Demonstrated improved detection capabilities for slow and weakly moving targets.
• Exhibited enhanced robustness in cluttered environments.

Conclusions:

• The novel three-step CSAR MTD scheme effectively mitigates strong clutter and significantly reduces PFA.
• The DLRVP test provides a powerful tool for discriminating true targets from isolated strong scatterers.
• The method offers a robust solution for reliable moving-target detection in complex radar scenarios.