Microwave Photonic ISAR Imaging Algorithm Based on Improved TSPN-TV-ADMM Algorithm

The Microwave Photonic Inverse Synthetic Aperture Radar (MWP-ISAR) typically necessitates an extended synthetic aperture time to achieve optimal range resolution. Coherently accumulating MWP-ISAR echoes over extended azimuth apertures is challenging due to the combined impact of target scattering and motion errors. Current processing methods for circular Synthetic Aperture Radar (CSAR) and large-angle ISAR often compromise azimuth resolution by selecting optimal imaging apertures or employing incoherent accumulation of sub-apertures, which is unsuitable for the ultra-high-resolution imaging goal of MWP-ISAR. To address these challenges, this paper presents a novel MWP-ISAR imaging algorithm leveraging the low-rank sparse characteristics of the echo matrix. The derivation of the matrix form under the azimuth data missing model is outlined, followed by a rigorous proof of the matrix’s sparse low-rank characteristics and the establishment of an imaging model. The proposed algorithm employs the Alternating Direction Method of Multipliers (ADMM) solution method based on truncated p-norm to address the model, and introduces the CTV norm to enhance edge information and improve imaging quality. The algorithm effectively restores missing azimuth echo data, ensuring high-quality imaging for MWP-ISAR. Measured data confirm the effectiveness of the proposed algorithm.