On the use of Least-Squares Lattice structures for missing data in ISAR imaging

In this work, we consider the spectral estimation of the gapped data encountered in inverse synthetic aperture radar (ISAR) imaging. For the estimation of missing data, we propose the use of Least-Square Lattice (LSL) Filters. The proposed method consists of interpolating the rows of two-dimensional backscattered data, where each row corresponds to the backscattered target data from a specific aspect angle. IFFT processing yields the enhanced spectral estimate of interpolated data. To demonstrate the effectiveness of the proposed algorithm, numerical results based on simulated data are presented.