基于RSSI－LQI的混合测距算法的研究

摘要

基于RSSI的测距技术因其成本低、易实现等优点被广泛应用于定位技术中。在常用的测距模型中，测距精度受到接收信号强度值RSSI以及环境参数值A、n的影响。针对RSSI的值受到外界环境因素影响导致接收数值波动较大，而环境参数是随着测量距离变化而改变的随机值等问题，提出了基于RSSI－LQI的混合测距算法。该算法通过引入链路质量指示（LQI）概念，首先对接收的RSSI值和LQI值进行高斯滤波，通过分析RSSI与LQI的衰落曲线，采用分段、加权的方法对曲线进行拟合，修正RSSI的值；同时利用最小二乘分段曲线拟合算法，修正环境参数A、n，从而提高定位精度。在井下环境进行实验，实验结果表明，在15m的测距实验中，采用改进的测距算法可以将相对误差百分比降到10％以下。%Commonly used models ranging shadowing,received signal strength indication and environmental parameters A and n directly affect the accuracy of the results.RSSI is easily affected by external environmental factors,cause the value fluctuations.Environmental parameters are not fixed values,but with changes in the distance measurement is changed.To solve these problems,introducing the link quality indication (LQI) Concept by using RSSI and LQI mix ranging algorithm, which wil deal with the value of RSSI and LQI through gaussian filtering and their decline curves to revised the RSSI val-ue,and using Least-squares piecewise curve fitting algorithm revised environmental parameters A and n.