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High-Resolution Imaging and 3-D Reconstruction of Precession Targets by Exploiting Sparse Apertures

Inverse synthetic aperture radar (ISAR) imaging of a precessing target, which is a kind of fast spinning target, is faced with migration through range cell when using traditional imaging algorithms. Theory of compressed sensing (CS) suggests that exact recovery of an unknown sparse signal with an overwhelming probability can be achieved from very limited number of samples. A cycle shift smoothed L0 algorithm based on CS is proposed in this paper for high-resolution ISAR imaging of precessing targets by exploiting sparse apertures. A precessing cone-shaped target model is built and a 3-D reconstruction method based on multistatic ISAR is proposed. Simulations and electromagnetic computation verify the validity of the proposed method.