Polarization Clutter Suppression for Maxmizing Signal-to-Clutter Ratio under Linear Constraints

The detection of ultra-low-altitude unmanned aerial vehicles (UAVs) poses significant challenges, primarily due to their low flight altitude, making them highly susceptible to severe interference from complex ground clutter. To address this issue, this paper proposes a multi-channel fusion polarization clutter suppression method based on fully polarimetric radar, effectively mitigating complex ground clutter. The proposed algorithm first performs a weighted fusion of the four polarization channel information from the fully polarimetric radar. Subsequently, Under the linear constraints, based on the optimization criterion of maximizing the signal-to-clutter ratio (SCR), a genetic algorithm is utilized to approximate the optimal solution of the objective function, thereby effectively suppressing complex clutter. Finally, the effectiveness of the proposed algorithm is analyzed and verified using field-measured radar data. The results demonstrate that the proposed algorithm improves the signal-to-clutter ratio by an average of 22.92 dB compared to single-polarization channels, providing a valuable reference for the polarization suppression of complex ground clutter and enhancing the accuracy of low-altitude UAV polarization detection.