基于改进高斯滤波与加权环境参数自适应估计的定位方法  

Location method based on improved Gaussian filter and adaptive estimation for weighted environment parameter

作　　者：杨晔晨 胡越黎[1,2,3] 徐杰 承文龙[1,2] 郁怀波 YANG Yechen;HU Yueli;XU Jie;CHENG Wenlong;YU Huaibo(Microelectronics Research and Develop Center,Shanghai University,Shanghai 200444,China;Shanghai Key Laboratory of Power Station Automation Technology,Shanghai 200444,China;School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China)

机构地区：[1]上海大学微电子研究与开发中心,上海200444 [2]上海市电站自动化技术重点实验室,上海200444 [3]上海大学机电工程与自动化学院,上海200444

出　　处：《上海大学学报（自然科学版）》2019年第5期701-711,共11页Journal of Shanghai University:Natural Science Edition

摘　　要：基于接收信号强度指示(received signal strength indication,RSSI)测距的定位技术是一种成本比较低廉的定位技术.为了能够有效降低RSSI值因环境因素的影响而产生的误差,提出了一种改进的加权高斯滤波算法对RSSI值进行处理;并建立了一种加权环境参数自适应估计算法对当前待定位的移动节点所处位置的环境参数进行估计;然后根据估计所得的环境参数确定移动节点所在位置的路径损耗模型;最后根据该模型估计移动节点的位置.实验结果表明,该方法能够有效提高系统的定位精度.Location technology based on received signal strength indication (RSSI) ranging is a kind of low-cost location technology. In order to reduce the error of RSSI value due to environmental factors, this paper proposes an improved weighted Gaussian filtering algorithm which is used to deal with the RSSI value, and it also proposes an adaptive estimation algorithm for weighted environment parameter which is used to estimate the environmental parameters of the place where the mobile node to be located is. Then the path loss model is determined by the estimated environment parameters, and the location of the mobile node is estimated by the model. Experimental results show that the method can effectively improve the positioning accuracy of the system.

关 键 词：RSSI测距 改进的加权高斯滤波 加权环境参数 自适应估计 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]