Sparse Multi-Channel Synthetic Aperture Radar Based Motion Induced Distortion Correction and Classification of Maritime Scenes

Multi-channel Synthetic Aperture Radar (MSAR) in the maritime environment has proven to be an effective technique for improved image fidelity and scene characterization. Past demonstrations of MSAR-based methods for improvements such as motion induced distortion correction and image classification were performed using a uniformly spaced array of phase centers. In this paper, we derive novel extensions of these techniques to the case of sparse and non-uniformly spaced phase center configurations and demonstrate their effectiveness for a variety of platforms and sensor arrangements. We establish general techniques for correcting motion induced distortions, establish theoretical bounds of performance, and empirically validate our techniques on data derived from our airborne MSAR system. We then use these images to characterize the structure of the maritime scene using our MSAR-based classification technique. Our imaging and classification techniques are amenable to efficient implementation on diverse hardware platforms and sensor arrangements, and thus can find ready application in practical multichannel radar systems.