RSSI信号的滤波分析及仿真

摘要

In wireless sensor networks,ranging technology based on RSSI (signal strength indication) is a low cost, low complexity measurement technology, but the RSSI signal is easily affected by environmental factors, So even in the same position point of the RSSI signal strength value is also greatly different, impact on accurate determination of position.First of all, the paper analyzes the principle of RSSI distance measurement , and several common filtering methods of RSSI signal. And using MATLAB software to generate RSSI signals through the model simulation , and then using the mean filter, Gauss filter, as well as Kalman filter to process the RSSI sampling value.The simulation results show that the error of Gauss filter and Kalman filter is obviously smaller than that of the mean filter in the presence of small probability and large disturbance;Due to the impact of the number of sampling points, the stability of mean filter and Gauss filter is not as good as Kalman filter.%在无线传感网中,基于RSSI(信号强度指示)的测距技术是一项低成本的、低复杂度的测量技术,但是RSSI信号容易受环境因素的影响,所以即便在同一位置点采集到的RSSI信号强度值也大不相同,影响位置的准确判定.论文首先分析了RSSI的测距原理,以及RSSI信号几种常见的滤波方法.并用MATLAB软件通过模型仿真产生RSSI信号,然后分别采用均值滤波、高斯滤波、以及卡尔曼滤波对RSSI采样值进行处理.仿真结果表明,小概率大干扰存在情况下,高斯滤波及卡尔曼滤波的误差明显小于均值滤波;均值滤波和高斯滤波因受采样点个数的影响,故稳定性不如卡尔曼滤波好.