2009/09/29 by Joey Wilson, Wilson, Joey, Neal Patwari +1
Computer Science · #FOS: Computer and information sciences #Other Computer Science (cs.OH) #cs.OH
paper · pdf · doi:10.48550/arxiv.0909.5417
This paper presents a new method for imaging, localizing, and tracking motion behind walls in real-time. The method takes advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network. Using a multipath channel model, we show that the signal strength on a wireless link is largely dependent on the power contained in multipath components that travel through space containing moving objects. A statistical model relating variance to spatial locations of movement is presented and used as a framework for the estimation of a motion image. From the motion image, the Kalman filter is applied to recursively track the coordinates of a moving target. Experimental results for a 34-node through-wall imaging and tracking system over a 780 square foot area are presented.