Abstract

To achieve the high-resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems, and the imaging results can be improved. To solve these problems and improve the image quality, the problem of ISAR imaging is termed as a block-sparse signal recovery problem by utilizing the block-sparse structure of the ISAR images. A localized low-rank promoting (LLP) method is introduced and extended to the complex case for the recovery of range compressed block-sparse signals. The sparse recovery problem is solved by minimizing another function, which is the surrogate function that can be solved more effectively. Based on the LLP method, the coefficients of the range compressed echo signal are reconstructed and some 2 × 2 matrices can be obtained. And then the log-determinant function is introduced to find the low rankness solutions for these matrices. Then the LLP method is also used in the cross-range domain to reconstruct the ISAR image. Experimental results show that the proposed method can recover better focused and higher quality ISAR images compared with the traditional methods.

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