Local Optimal Matching Algorithm for Subaperture Imaging of Squint Synthetic Aperture Radar

Squint Synthetic Aperture Radar (SAR) can observe the side-front or side-rear scene of the platform. The squint mode improves the observation area and flexibility of SAR greatly. For subaperture imaging of squint SAR, a Local Optimal Matching Algorithm (LOMA) is proposed in this paper. In the algorithm, a new criterion is used in the presentation of the functions for range cell migration correction, secondary range compression and compensation in azimuth frequency domain. The criterion is that the target located at the azimuth frequency is matched optimally. It is different from the traditional algorithm, whose criterion is that the target at the azimuth center is matched optimally. Based on the new criterion, the proposed algorithm is able to avoid the mismatching and improve the focusing of the targets far from the azimuth center. The validity of the proposed algorithm is illustrated by the simulation results.