Graph Laplacian-based Indoor Radio Tomographic Imaging using LOS Components Estimation

Radio tomographic imaging (RTI) is a technique for estimating a spatial loss field (SLF), which is the quantified attenuation of radio signals within an observation area by analyzing radio signals. Our study focuses on RTI techniques for indoor smart factory environments with multiple access points (APs) and automatic guided vehicles (AGVs) equipped with wireless terminals. RTI techniques perform poorly in factory environments due to severe multipath channels. In this study, to improve the performance of RTI, we propose the graph Laplacian-based RTI method using LOS (Line-of-Sight) components estimation. LOS components correspond to the received powers of the direct paths. The SLF is represented by dividing the observation area into multiple pixels, and the spatial correlation between the pixels is expressed using the graph Laplacian. We evaluated the performance of the proposed method using simulation experiments.