基于RSSI测距算法改进的研究  

作　　者：徐登彩[1] 周奇年[1] 张振浩[1] 

机构地区：[1]浙江理工大学信息电子学院,浙江杭州310018

出　　处：《工业控制计算机》2013年第5期72-73,75,共3页Industrial Control Computer

摘　　要：基于RSSI测距技术因其低成本和低复杂度的优点而被广泛应用于无线传感网络(Wireless Sensor Network,WSN)的定位技术中。但是电磁波在实际环境中的传播由于易受到诸如多径、绕射、吸收等现象的影响而造成较大的测距误差。针对这一问题,提出了利用最小二乘法曲线拟合来构建实时测距模型,并采用卡尔曼滤波处理RSSI值,此外引入链路质量结合RSSI实现分段处理的测距算法。实验结果表明,经过改进的算法的测距精度和抗干扰能力相比其他原有的算法有了较明显的提高。Ranging Technology base on Received Signal Strength Indicator is widely used in WSN Location because of low cost and low complexity.But relatively large errors could produce with the impact of some environment phenomenon such as multipath,diffraction,absorption.To solve this problem,this paper point to construction of the real time measurement model by using Least squares method,furthermore,using Kalman filter to processed the value of RSSI,in addition introduces link quality combined with RSSI realize sectional Ranging algorithm.Experimental results show that the ranging accuracy.

关 键 词：无线传感网络 RSSI LQI 最小二乘法 卡尔曼滤波 

分 类 号：TN929.5[电子电信—通信与信息系统] TP212.9[电子电信—信息与通信工程]