Improvement and implementation of maximum likelihood estimation positioning algorithm based on RSSI
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摘要:
针对基于RSSI(接收信号强度指示)的极大似然估计算法会出现消去二次项时坐标信息丢失,定位误差较大的问题,提出了一种改进的基于RSSI极大似然估计的定位算法.该算法先用卡尔曼滤波算法对采集到的RSSI进行数据处理,然后利用在极大似然估计算法中使用基于泰勒级数展开的最小二乘法对未知节点求解定位.仿真实验结果表明,该算法改善了原算法定位的稳定性,有效减小了定位误差,提高了定位精度.
In order to solve the problem that the maximum likelihood estimation algorithm based on RSSI（Receiving Signal Strength Indicator）will lose coordinate information when the quadratic term is eliminated,and have large positioning error,an improved location algorithm was proposed based on RSSI maximum likelihood estimation.Firstly,the collected RSSI values were processed by Kalman filtering algorithm,and then the unknown nodes were located by using the least square method based on Taylor series expansion in the maximum likelihood estimation algorithm.The simulation results show that the improved algorithm has improved the stability of the original algorithm,effectively reduced the location error,and improved the location accuracy.
作者:
詹华伟 詹海潮 赵勇
Zhan Huawei;Zhan Haichao;Zhao Yong(College of Electronic and Electrical Engineering,Key Discipline Open Laboratory of Electromagnetic Wave Characteristic Information Detection of Henan Province,Henan Normal University,Xinxiang 453007,China)
机构地区:
betway官方app 电子与电气工程学院河南省光电传感集成应用重点实验室
出处:
《betway官方app 学报：自然科学版》 CAS 北大核心 2018年第5期37-41,共5页
基金:
河南省科技攻关项目(172102210336) 河南省教育厅科学研究重点项目(17B510004)
关键词:
接收信号强度指示 卡尔曼滤波 极大似然估计 泰勒级数
received signal strength indicator Kalman filtering maximum likelihood estimation Taylor series
分类号:
TP301.6 [自动化与计算机技术—计算机系统结构]
