Imaging of maneuvering targets based on parameter estimation of multicomponent polynomial signals

We discuss ISAR imaging of maneuvering targets based on modeling the ISAR data as multicomponent polynomial signals with arbitrary amplitude. The proposed algorithm estimates polynomial signal components one by one by using the "clean" technique. The polynomial coefficients and amplitude of each component are estimated by using product high-order ambiguity function and a low-pass filtering step. The estimated parameters are used to reconstruct the dynamic radar images of maneuvering targets. Compared with the existing algorithm, the proposed imaging algorithm is computationally efficient. Excellent results have been obtained in imaging experiments on real ISAR data.