基于RSSI的混合滤波算法

Hybrid Filtering Algorithm Based on RSSI

基于接收信号强度指示(Received Signal Strength Index,RSSI)的测距技术因其低成本及低复杂度被广泛用于无线传感网络(WSN)定位技术中。由于RSSI值易受环境的影响,即使在同一位置采集到的RSSI值也会出现波动、突变,从而导致测距结果误差较大。在分析RSSI测距原理和当前常见的滤波算法的基础上,通过实验比较单一滤波的效果,综合单一滤波的优势,提出了一种基于狄克逊检验法滤波、中位值滤波及高斯滤波的混合滤波算法。实验首先利用线性回归算法优化RSSI测距模型的参数,再通过混合滤波过滤异常RSSI值来获得最优值,以实现准确测距。实验结果显示,与单一的滤波算法相比,混合滤波算法能明显减小RSSI值的波动,更为有效地剔除异常RSSI值,且滤波后的RSSI值更接近理想值,测距误差更小,证明了混合滤波算法是有效且可行的。

Received signal strength index(RSSI)based ranging technology is widely used in wireless sensor network(WSN)positioning technology,because of its low cost and low complexity.The RSSI value is easily affected by the environment,even if the RSSI value collected at the same location is subject to fluctuations and abrupt changes,thus the ranging error is large.Based on the analysis of RSSI ranging principle and the current common filtering algorithm,this paper proposed a hybrid filtering algorithm based on Dixon test filtering,median filtering and gaussian filtering by comparing the effect of single filtering through experiments and taking advantage of the significant effect of filtering.Firstly,the linear regression algorithm is used to optimize the parameters of the RSSI ranging model,and then the optimal value is obtained by filtering the abnormal RSSI value through the hybrid filter to achieve accurate ranging.The experimental results show that compared with a single filtering algorithm,the hybrid filtering algorithm can significantly reduce the fluctuation of the RSSI value,and eliminate the abnormal RSSI value more effectively.The filtered RSSI value is closer to the ideal value,and the ranging error is smaller.It proves that the hybrid filtering algorithm is effective and feasible.