基于DS证据理论的室内移动目标RSSI定位算法

为使WiFi无线传感器网络能够利用单次获取的接收信号强度指示（Received Signal Strength Indication，RSSI）快速定位目标并减小RSSI阴影衰落对定位的影响，提出一种改进的基于Dempster-Shafer（DS）证据理论的利用RSSI信息对室内移动目标定位（Locating Indoor Mobile Target with RSSI based on DS evidence theory，LIMT-DS）的方法。LIMT-DS方法根据传感器接收到的RSSI值构造关于目标位置估计的条件概率密度函数，并据此通过改进的证据构造方法生成各传感器关于定位环境中位置点的证据，对各位置点进行证据综合，最后通过改进的决策模式选择出目标存在可能性较大的数个定位点进行位置加权，获得目标的位置估计。仿真与实验结果表明，LIMT-DS方法可以用传感器网络单次获得的RSSI信息实现对目标的定位，其定位性能明显优于同类方法。 

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.