Maximum-likelihood ISAR image autofocusing technique based on instantaneous frequency estimation

The authors consider the problem of motion compensation in the inverse synthetic aperture radar (ISAR) imaging technique. A novel autofocusing technique based on maximum-likelihood (ML) estimation of the focusing parameters is proposed. The likelihood function is computed by using as observed data samples of the instantaneous frequency (IF) of the received signal. A statistical analysis of the IF is performed, both to determine the likelihood function and to define a criterion for the choice of IF samples to be processed. The effectiveness of the autofocusing algorithm is shown by presenting and discussing some simulation results