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Based on the linear relationship between the chirp rate of cross-range inverse synthetic aperture radar (ISAR) signal and the slant range, a parametric sparse representation method is proposed for ISAR imaging of rotating targets. The ISAR echo is formulated as a parametric joint-sparse signal and the chirp rates at all range bins are estimated by maximizing the contrast of sparse ISAR image. Comparing...
A novel high resolution ISAR imaging method based on adaptive sparse recovery is proposed in his paper. The ISAR signal in each range bin is sparsely represented by an over-complete chirplet basis matrix, which can be determined by an unknown parameter set. An adaptive parametric sparse recovery method is proposed to retrieve both the parameter set and the ISAR image. This goal is achieved by sequentially...
The ISAR imaging problem can be converted to a sparse recovery problem and efficiently solved by a weighted L1 minimization algorithm, which outperforms the regular L1 minimization substantially, provided the sparse representation is already known. However, the sparse representation of the ISAR signal is related to the target rotation rate, which is usually unknown for noncooperative target. In this...
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