Clutter Suppression and Weak Target Detection Using EEMD-WOA Algorithm for FMCW Radar

Weak target detection poses a significant challenge in FMCW radar systems due to substantial near-range clutter. Conventional MTI algorithms and clutter map methods rely on the intensity and doppler frequency differences between the clutter and the moving target in multiple data frames. However, the suppression performance becomes inadequate when the clutter intensity is substantial and the multipath effect is significant. Additionally, feeble target leakage occurs and target detection is impaired following clutter suppression. This paper presents a joint EEMD-WOA processing framework that addresses the abovementioned issues. The framework eliminates clutter by employing ensemble empirical modal decomposition (EEMD) of multi-frame signals to extract the signal subspace. Additionally, the whale optimization algorithm (WOA) is utilized to extract signals by exploiting the disparity in higher-order statistics between the clutter and the targets, thereby accomplishing the objective of weak target detection. Simulation analysis substantiates the superior detection performance of this method in comparison to alternative methods.