A Real-Valued Approximate Message Passing Algorithm for ISAR Image Reconstruction
Compressed sensing (CS) theory describes the signal using space transformation to obtain linear observation data selectively, breaking through the limit of the traditional Nyquist theorem. In this paper, we aim at accelerating the current approximate message passing (AMP) and propose an approach named real-valued AMP (RAMP) for faster and better inverse synthetic aperture radar (ISAR) imaging reconstruction. The azimuth dictionary is first processed with real. We then use matrix processing to solve the AMP vector iterative method, by utilizing the relation between the quantification of matrix product and the Kronecker product. The experimental results are presented to demonstrate the validity of this method.
KeywordsInverse synthetic aperture radar (ISAR) Image compressed sensing Approximate message passing
This work was supported in parts by the National Natural Science Foundation of China (no. 61301211), the Postgraduate Education Reform Project of Jiangsu Province (no. JGZZ17_008), and the Postgraduate Research and Practice Innovation Program of Jiangsu Province (no. KYCX18_0295).
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