Abstract
ABSTRACTIn order to obtain a high-resolution and well-focused image from compressively sampled echo data in the presence of wall ambiguity, a parametric sparse representation algorithm is proposed in this paper. A parametric dictionary with an unknown wall parameter is designed to represent the wall’s ambiguity. Then, imaging through unknown walls problem is converted into a joint optimization one which can be decomposed into sequential sparse imaging and wall parameter estimation. Specifically, the wall parameter estimation is performed by searching the maximum contrast. Numerical results are presented to demonstrate the validity and effectiveness of the proposed algorithm.
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