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针对室内接收信号强度指示(RSSI)测距定位中,测距精度较低、易受环境影响的问题,提出了一种基于对数鲁棒函数(LnRLS)的UKF改进算法,有效改善测距误差,提高定位精度。在室内环境下,首先采用卡尔曼滤波对接收到的RSSI值进行预处理,运用最小二乘法拟合传播方程,使用改进的UKF算法对数据进行二次处理得出测量距离,通过三边定位算法估计节点坐标。将实验结果与其他文献采用的传统UKF测距算法及室内定位方法相比,改进算法将测距误差降低了14.4%,有效的减少测距误差,提高室内定位系统的定位精度。
In order to solve the problem of low precision and easily influenced by environment in indoor RSSI location measurement, a UKF improved algorithm based on logarithmic robust function (LnRLS) is proposed to effectively improve the ranging error , Improve the positioning accuracy. In the indoor environment, the received RSSI value is firstly preprocessed by Kalman filter, the propagation equation is fitted by the least squares method, the data is processed by the improved UKF algorithm for the second time to obtain the measured distance, and the three-sided positioning algorithm Estimate the node coordinates. Compared with the traditional UKF ranging algorithm and indoor positioning method adopted in other literatures, the improved algorithm reduces the ranging error by 14.4%, effectively reduces the ranging error and improves the positioning accuracy of the indoor positioning system.