Enhancing indoor radio tomographic imaging based on interference link elimination

Radio tomographic imaging (RTI) is a promising technique to localize and track the target without wearing any electronic device. However, the performance of traditional shadowing-based RTI (SRTI) degrades in indoor environments due to the existence of interference links caused by multipath. The interference links can bring false spots in the imaging results of RTI and make the true spot drift, resulting in position estimation error of the target. In this paper, we propose an interference link canceling technique to improve the performance of RTI where temporal and spatial properties of shadowed links are jointly used to detect the interference links. Since the spatial detection relies on the prior knowledge of the position of the target, we use Kalman filter to provide the position estimation. Moreover, a mean-shift clustering method is adopted to obtain the initial position estimation of the target. The experimental results demonstrate that the proposed enhanced SRTI (ESRTI) method outperforms the existing methods in terms of both image quality and tracking accuracy.