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Sparsity-based image reconstruction techniques for ISAR imaging

We present novel techniques for ISAR imaging via a Sparsity-based image reconstruction methodology. The latter offer a distinct advantage of Fourier based reconstruction techniques by offering the flexibility of using different basis functions to represent the underlying scene structure being imaged. We derive our ISAR algorithm in detail and present experimental results on real ISAR data showing its superiority over traditional Fourier based image reconstruction. We also demonstrate how our formulation of the ISAR imaging problem overcomes some of limitations associated previous approaches to CS (Compressive Sensing) based ISAR imaging in the literature.