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Due to the great computation load and memory cost of the matrix-vector multiplication, the sparse reconstruction algorithms are severely limited in the applications of radar imaging with real data. In order to solve this problem, we construct a backprojection-based range–azimuth decoupled operator (BP-RADOp) and combine the complex approximate message passing algorithm (CAMP) with it. We call this...
As the effective means for achieving sparse microwave imaging, sparse reconstruction algorithms (SRAs) can be generally classified into four main categories: greedy pursuits, ℓ1-norm minimization, nonconvex optimization and Bayesian framework. In this paper, we compare the performance of the typical SRAs in synthetic aperture radar (SAR) imaging. We consider four algorithms including the orthogonal...
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