Abstract
For the conventional Inverse synthetic aperture radar (ISAR) imaging, the observation durations must be long enough to achieve high cross-range resolution. However, it is often impossible to achieve enough echo samples in cross-range, making the imaging result with poor resolution. Compressed sensing (CS) is a new approach of sparse signals recovered. In this paper, a high resolution ISAR imaging method for sparse pulses based on CS method is presented. It shows that the image of sparse targets can be reconstructed by solving a convex optimization problem based on l 1 norm minimization with only a small number of ISAR echo samples. The simulation results show that the CS imaging approach outperforms the range-Doppler one in resolution with limited data.
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