基于平方根容积卡尔曼滤波的RSSI定位参数估计算法.PDFVIP

26 1 © Vol. 26 No. 1 2014 1 Journal of System Simulation Jan., 2014 RSSI ( 100044) (RSSI) RSSI RSSI (SCKF) SCKF RSSI (RSSI) (SCKF) TP391.9 A 1004-731X (2014) 01-0119-06 Received Signal Strength Indicator Parameter Estimation Algorithm Based on Square-root Cubature Kalman Filter LIU Ying, SU Jun-feng, ZHU Ming-qiang (School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China) Abstract: When wireless signal is used for indoor localization, due to the complex environment of multi-path effects, there is no consistent relationship between the signal strength received by the receiving nodes and the distance from the receiving nodes to the receiving nodes, so there is a larger localization error for the Received Signal Strength Indication RSSI) in the indoor environment. A new received signal strength indicator parameter estimation algorithm based on square-root cubature kalman filter was proposed, this algorithm converted the RSSI localization problem into the parameter vector estimation problem of nonlinear equations, which utilized the Square-root Cubature Kalman filter (SCKF) to estimate the target’s position and the RSSI channel attenuation parameter simultaneously, and uses dynamic channel parameter to correct the node’s position in real – time. The experimental results demonstrate that the RSSI