Autoregressive Model-Based Particle Swarm Optimization Algorithm for Main Lobe Jamming Suppression in Phased Array Radar

This paper proposes a novel blind extraction method based on autoregressive (AR) model and particle swarm optimization (PSO). By constructing an AR model of the transmitted signal and optimizing the extraction vector via PSO, the algorithm achieves effective suppression of main lobe jamming without prior knowledge of jamming characteristics. Simulations demonstrate that the proposed method outperforms classical blind separation techniques (e.g., JADE and FastICA) in terms of signal-to-interference-plus-noise ratio (SINR) improvement and computational efficiency, particularly in low-SNR scenarios.