High-Resolution ISAR Imaging of Maneuvering Targets Based on Azimuth Adaptive Partitioning and Compensation Function Estimation

An important challenge in high-resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is the 2-D spatial-variant (SV) high-order phase error. The classic autofocusing phase correction method cannot effectively correct the SV phase error, which makes it difficult for the traditional range-Doppler (RD) algorithm to obtain high-quality images in high-resolution imaging. The range SV phase error can be compensated for each range cell separately after migration correction of the cross-range cell, but correcting the azimuth SV phase error is challenging. This article presents a high-resolution ISAR imaging algorithm for maneuvering targets with azimuth adaptive partitioning and phase compensation function estimation. First, the coarse-focus image is obtained by the azimuth Fourier transform (FT) after translational motion compensation and migration through range cell (MTRC) correction. Then, the azimuth coarse-focusing result is adaptively partitioned at each range bin. Each partitioned data block is transformed into the time domain, and joint time-frequency analysis (JTFA) is performed to obtain the time-frequency (TF) curve of the signal. Through alignment of TF curves, the phase compensation function is inverted. Finally, the corrected subblocks are stitched together to obtain high-quality ISAR images. ISAR imaging experiments with simulated and real data demonstrate the effectiveness and practicability of the proposed algorithm in high-resolution ISAR imaging of maneuvering targets.