Motion Compensation for OFDM Inverse Synthetic Aperture Sonar Imaging Based on Compressed Sensing

Inverse synthetic aperture sonar (ISAS) is the major instrument to observe moving underwater vehicles with high-resolution acoustic images. In this article, we consider the cyclic prefix (CP)-based orthogonal frequency-division multiplexing (OFDM) ISAS imaging for a noncooperative underwater vehicle. Compared to the ISAS using the conventional linear frequency-modulated (LFM) waveform, the OFDM signal is more sensitive to Doppler shifts/errors. The fluctuation of acoustic velocity in the propagating medium brings random phase errors and leads to heavily blurred images. Existing ISAS imaging methods are based on the translational motion of the target, and these methods suffer from defocusing in severe ocean conditions. In this article, we propose the motion compensation algorithm for the OFDM ISAS imaging to minimize the effect of velocity variations caused by ocean turbulence. The sparsity of the ISAS image is utilized as a global metric for the phase error estimation and image generation by constructing an l(1)-norm optimization. It is demonstrated that inter-range-cell interference (IRCI)-free ISAS images can be obtained no matter whether there are phase errors and/or strong noise. Simulation results indicate the effectiveness of the proposed method.