ISAR range alignment by minimizing the entropy of the average range profile

In this work, a novel approach to global range alignment for the inverse synthetic aperture radar (ISAR) imaging is presented. The algorithm is based on the minimization of the entropy of the average range profile (ARP), and the processing chain is capable of exploiting the efficiency of the FFT. No parametric model for the relative offset amongst the range profiles is required, which eliminates the necessity of the exhaustive search operation. The derivation of the algorithm indicates that the presented methodology is essentially an iterative solution to a set of simultaneous equations, and its robustness is also ensured by the iterative approach. Some alternative criteria, such as the ARP contrast maximization, can be introduced into the algorithm just with minor change in the entropy based method. The convergence and robustness of the presented algorithm have been validated by the simulated and experimental ISAR data processing results.