A Multisource Fusion System for Through-Wall Radar Compensation Using LiDAR and SLAM-Based 3-D Reconstruction

With the acceleration of urbanization, Through-Wall Radar (TWR) technology has become crucial for military reconnaissance and disaster emergency response. However, conventional TWR systems predominantly adopt oversimplified homogeneous wall models in their compensation algorithms, which fail to account for the inherent heterogeneity of real-world building walls. To mitigate the impact of irregularities such as doors, windows, pillars, and protrusions on non-uniform building walls during through-wall imaging, this paper proposes a multi-source fusion system and a wall compensation method based on Light Detection and Ranging (LiDAR) point cloud data. By integrating measurements from both LiDAR and TWR, and employing Simultaneous Localization and Mapping (SLAM) technology along with point cloud preprocessing and contour fitting techniques, the system generates accurate wall contour information, enabling effective compensation. Experimental results show that the accuracy of building interior layout reconstruction is significantly improved by compensating for the effects of external wall irregularities extracted from LiDAR data.