SAR imaging of multiple ships based on compressed sensing

Recent theory of Compressed Sensing (CS) gives us a novel version that an unknown sparse signal can be exact recovery with overwhelming probability beyond Nyquist sampling constraints. In this paper, we adapt this idea and present a framework of high-resolution synthetic aperture radar (SAR) imaging with multiple ships. Under the framework, we convert the multiple ships imaging into a problem of sparse signal reconstruction with certain orthogonal basis, hence the sparse reconstruction of CS can be fulfilled and a theoretical upper bound of the cross-range resolution is presented. Real data results verify the effectiveness of the CS imaging framework.