A Novel ISAR Multi-Target Separation and Imaging Algorithm Based on Radon Transform and RPCA

Inverse Synthetic Aperture Radar (ISAR) enables detection and identification of non-cooperative maneuvering targets (e.g., aircraft, satellites, and marine vessels) through echo signal processing. However, conventional ISAR imaging methods face challenges in multi-target scenarios due to differing motion parameters among targets within the same radar beam. Direct processing of mixed echoes using traditional approaches often fails to achieve focused imaging. To address this issue, this paper proposes a novel ISAR multi-target separation and imaging algorithm integrating Radon transform and Robust Principal Component Analysis (RPCA). The method effectively separates and focuses on targets under multi-target interference. Simulation experiments validate the effectiveness of the proposed algorithm. This work provides a practical solution for complex multi-target ISAR imaging applications.