An Improved CLMD Algorithm for Micro-Motion Target Imaging in ISAR

Inverse Synthetic Aperture Radar (ISAR) enables high-resolution imaging of non-cooperative moving targets under all-weather and all-day conditions, playing a critical role in target feature extraction and identification. However, micro-motion targets, characterized by subtle and complex motion characteristics, pose significant challenges to conventional ISAR imaging techniques. This paper establishes a wideband radar echo signal model for micro-motion targets and proposes an improved Complex Local Mean Decomposition (CLMD) algorithm based on peak detection and sliding window techniques. This approach accurately separates micro-Doppler(m-D) signals from the radar echoes. Subsequently, Range Cell Migration Correction (RCMC) is applied to the separated main body echoes to facilitate ISAR imaging. Simulation results demonstrate the feasibility and effectiveness of the proposed algorithm in enhancing imaging quality.