Building layout reconstruction via sparsity constraint in wall reverberation environment

In the field of through-the-wall radar imaging, existing compressive sensing (CS) methods mainly concentrate on deriving indoor targets image while overlooking the reconstruction of building layout image. In this paper, we focus on the problem of utilizing CS for building layout reconstruction (BLR) in wall reverberation environment. Specifically, first, by incorporating the characteristics of building layout, an extended target CS imaging model in wall reverberation environment is established. Then, an extended-target-based group block CS (ET-GBCS) algorithm based on the alternating direction multiplier method is proposed to accurately reconstruct the building layout. After obtaining the reconstructed result of each view, the total variation minimization method is used to process the multi-view fusion result for building layout edge preservation and image noise removal. Finally, the effectiveness of the proposed algorithm is verified by electromagnetic simulations.