A Fast HRRP Synthesis Algorithm with Sensing Dictionary in GTD Model
作者： Qun Wan , Rong Fan , Yipeng Liu , Hui Chen , Xiao Zhang
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摘要: To achieve high range resolution profile (HRRP), the geometric theory of diffraction (GTD) parametric model is widely used in stepped-frequency radar system. In paper, a fast synthetic algorithm, called orthogonal matching pursuit with sensing dictionary (OMP-SD), proposed. It formulates traditional HRRP to be sparse approximation problem over redundant dictionary. As it employs priori information that targets are sparsely distributed space, (SRP) can accomplished even presence data lost. Besides, computational complexity reduced by introducing (SD) and mitigates mismatch at same time. The computation decreases from O(MNDK) flops for OMP O(M(N +D)K) OMP-SD. Simulation experiments illustrate its advantages both additive white Gaussian noise (AWGN) noiseless situation, respectively.
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