Indoor Mobile Target Positioning Algorithm with RSSI Based on DS Evidence Theory

‍ ‍In order to enable WiFi wireless sensor networks to quickly locate the target by using received signal strength indication （RSSI） and reduce the impact of RSSI shadow fading on positioning， an improved method for locating indoor mobile target with RSSI based on Dempster-Shafer （DS） evidence theory （LIMT-DS） is proposed. According to the RSSIs received by sensors， the LIMT-DS method forms the conditional probability density functions of the estimate of target location， and with these functions， constructs the evidences of every sensor on every location point in positioning environment by using an improved evidence construct method， then combines all the evidences of each location point. Finally， an improved decision-making mode is used to select several likely positioning points for position weighting， and obtain the position estimation of the target. The experimental results show that the LIMT-DS method can locate the target using the single group of RSSI information obtained by the sensor network， its localization performance is obviously better than the similar methods.