A New Algorithm for Sparse Aperture Extrapolation

An algorithm for estimating full aperture with sparse data is proposed in this paper. For wide vacant aperture in sparse data, by measuring sparse data actually, accurate sparse data frequency domain energy distribution estimate can be obtained with parametric approaches. With estimated power spectrum as prior information, minimum weighted norm as the restraint, underdetermined equations are solved to interpolate vacant aperture, thus wide aperture data segment estimate is obtained. This algorithm can be effectively applied to ISAR imaging in sparse data. Resulting simulation and actual data processing results confirm validity of the proposed algorithm