Building Layout Imaging Method Using the Inter-block Coupling Sparse Bayesian Learning
JIN Liangnian①② FENG Fei② LIU Qinghua② OUYANG Shan②
①(Guangxi Key Laboratory of Wireless Wideband Communication & Signal Processing, Guilin 541004, China) ②(Institute of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China)
Abstract：In through-wall radar building layout imaging, the existing extended target sparse imaging method can not effectively exploit the structural sparsity of the wall reflections in the scene, resulting in incoherent imaging and unobvious contour of walls. A sparse Bayesian learning method is proposed for building layout imaging by exploiting the inter-block coupling of sparse signal. On the basis of the hierarchical Gaussian prior model of block sparse signal characteristics, the inter-block coupling coefficient is further used to characterize the structured sparsity of the wall reflections. Then these coefficients are introduced into the hyperparameters controlling the prior distribution of sparse signal, thus this structured sparsity is transformed into the coupling relationship of these hyperparameters. Susequently, an Expectation-Maximization (EM) algorithm is developed to infer the Maximum A Posterior (MAP) estimate of these hyperparameters. The results of simulation and experiment show that the proposed method improves effectively the imaging quality of the building wall.
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