Decoupled ISAR imaging using RSFW based on twice compressed sensing

Random stepped-frequency radar without delay-Doppler coupling can suppress the range ambiguity and become less sensitive to electronic countermeasures. Considering its inherent randomness, this paper focuses on sidelobe reduction in inverse synthetic aperture radar imaging for sparse target scenes based on the compressed sensing (CS) theory. First, precise motion compensation and a high-resolution range profile (HRRP) with a low sidelobe are simultaneously achieved by the CS scheme for each train containing fewer pulses. Then, we analyze the disadvantages of conventional cross-range compression algorithms, which cannot guarantee high-quality focusing performance because there may be some false HRRPs caused by the uncertainty of the CS theory or some other factors. Finally, the modified correlation coefficient is defined to discard a large percentage of those uncorrelated HRRPs and the cross-range resolution is achieved by using the CS theory again. The validity of this decoupled imaging algorithm is demonstrated by some simulation and experimental results, which indicate that the approach is capable of precise estimation of scattering centers and effective suppression of a high sidelobe.