Robust Radio Tomographic Imaging under Sensor Location Uncertainty

Radio Tomographic Imaging (RTI) has wide applications in detection and tracking of targets which does not require any sensor to be attached with the target, consequently it leads to device free localization. RTI is an application of wireless sensor network where all sensor nodes cooperatively send their received signal strength (RSS) data to central processing unit to yield imaging of targets in the wireless network. Hence, RTI forms based on cooperative communication. In previous literature it is observed that RTI uses RSS for imaging purposes but there is no consideration of uncertainty due to position variation of transceiver nodes. Considering these uncertain scenarios in RTI system how best we can detect and image the obstructing object is handled in this work. In the entire work the uncertainty is considered to have effects on the transition matrix W. There are three robust approximation solutions considered for handling the uncertainty and a comparison among all is studied. It is also verified from performance studies that the interval uncertainty has better SLF estimation performance than others and is also computationally less complex than the stochastic robust approximation as interval-based uncertainty is solved through linear programming.