Through-the-Wall Radar Building Layout Reconstruction with Size-Adaptive Block Sparse Constraint

Building layout reconstruction (BLR) with through-the-wall radar (TWR) mounted on an unmanned aerial vehicle (UAV) is challenged by clutter and the mismatch between fixed blocks and wall structures. This letter proposes a size-adaptive block-sparse method guided by mean information entropy (MIE). Candidate wall blocks are grown under range-resolution and MIE constraints, and then incorporated into a reweighted alternating direction method of multipliers (ADMM) reconstruction model. To our knowledge, this is the first work to formulate block partitioning for TWR-based BLR as an information-theoretic optimization problem. Simulations achieve the best peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and F1-score among compared methods, reaching 12.511 dB, 0.782, and 0.854, respectively. Field experiments using a UAV-borne linear frequency modulated continuous wave (LFMCW) TWR operating at 2.95 GHz with 500 MHz bandwidth further validate improved structural continuity and clutter suppression.