基于相位差测距的WSN节点测距数据滤波和定位算法的研究

摘要

Because of the large errors associated with the process of distance measurement,the range-based node localization technique is with low precision in wireless sensor networks (WSN).In this paper,the process of the "Phase of Arrival" (POA) ranging method is investigated.The statistical parameters describing the ranging results are presented and an algorithm to process raw measurement data is proposed,which makes significant improvement in ranging accuracy.Additionally,using the POA to measure the distance and Weighted Least Square Estimates(WLSE) to provide the initial localization,the paper proposes to apply Unscented Kalman Filter(UKF) algorithm to the precise node locating with POA as the observed quantity.The emulation has shown that the node localization accuracy is improved by using the UKF localization method to POA-Based position system.%在基于距离的无线传感网络定位系统中,测距精度对定位结果精度的影响非常大.文中研究了基于到达相位差(Phase of Arrive)测距技术的测距原理,对测距结果进行统计分析,并提出了针对到达相位差测距数据的滤波算法,有效提高了测距精度.文中在相位差测距和加权最小二乘法初始定位的基础上,将无迹卡尔曼滤波算法(UKF)应用到节点定位中.通过具体实验数据表明,基于相位差的UKF定位模型可以有效提高无线定位精度.