Joint ISAR imaging and azimuth scaling under low SNR using parameterized compensation and calibration method with entropy minimum criterion

Abstract In general, the method of conventional motion compensation for inverse synthetic aperture radar (ISAR) imaging is divided into translational (TMC) and rotational (RMC) in sequence. TMC premise most critical procedure range alignment. However, deviation echo correlation results poor performance alignment under low signal-to-noise ratio (SNR). Therefore, a new high-resolution ISAR azimuth scaling SNR using parameterized calibration proposed this paper. Firstly, target modeled, which modeled as formula polynomial coefficient vector. addition, entropy minimization corresponding to signal with term based on coefficients taken objective function. Moreover, particle swarm optimization (PSO) algorithm utilized search global optimal parameters be estimated precisely efficiently implement joint scaling. The experimental from both simulated real data verify effectiveness robustness method.