Inverse Synthetic Aperture Radar (ISAR) Imaging of Targets with Non-Uniform Motion and Constant Acceleration based on Compressed Sensing

Compressed sensing (CS)-based inverse synthetic aperture radar (ISAR) imaging usually considers the uniform motion of targets. However, in practical scenarios, the targets usually have non-uniform motion, which creates the time-varying Doppler frequency shift and the ISAR image is blurred. Also, the basis matrix used in CS-based ISAR imaging is related to the rotational motion parameters which should be estimated too. However, the targets are assumed to have cooperative behavior with respect to radar; that is the target motion is known a priori and parameter estimation is not considered. In this paper, an improved version of CS-based imaging for non-uniform motion with constant acceleration and non-cooperative targets is proposed and best sparse representation is extracted. Simulation results show that the proposed algorithm is more efficient than other methods even without rotational motion compensation and provide higher image contrast.