Quadrilateral model based Radio Tomographic Imaging in random Wireless Sensor Network

Radio Tomographic Imaging (RTI) is a popular technique for locating the target by using the characteristic that the Received Signal Strength (RSS) varies dramatically as the signal is obstructed by the target in Wireless Sensor Network (WSN). The existed works mainly rely on the establishment of linear models to locate the target by using the weight matrix in an elliptical model. This paper first gives an indoor environment with randomly distributed wireless sensors, and then proposes a linear model in a quadrilateral relating the changes of RSS to locate the target. In our approach, the Minimum Mean Square Error (MMSE) is utilized to construct the weight matrix for the linear model. Furthermore, the concept of pictures superposition is considered to process the images to enable the highly-accurate localization. The experimental results show that based on the proposed approach, the localization error in the single target situation is lower than 0.2 m by using the superposition of only five quadrilaterals.