Parameterized Translational Motion Compensation for ISAR Imaging under low SNR

In this paper, a new method for high-resolution ISAR imaging under low SNR using parameterized translational motion compensation is proposed. Firstly, translational motion of the target is modeled as formula of the polynomial coefficient vector. Then, entropy minimization corresponding to range profile with compensation term based on coefficients above is taken as objective function. Moreover, the Golden Section Search (GSS) is utilized to search the optimal parameters, which are estimated precisely and efficiently to implement motion compensation. Experimental results from both simulated and real data verify that the proposed method can achieve high-resolution fine focused ISAR image under low SNR with validity and robustness.