摘要
为提高定位算法的鲁棒性和定位精度,文章提出了一种基于最小二乘(LS)和泰勒级数(Taylor)的超宽带定位算法。首先利用最小二乘进行粗略定位,再通过阈值筛选和权重计算对初始数据进行寻优以获取最佳初值,最后通过Taylor算法对定位节点进行迭代求解,获取精准的位置坐标。仿真实验结果表明,此方法对固定/移动节点的定位误差控制在5 cm左右,可满足大多数严格的工业应用环境。
In order to improve the robustness and positioning accuracy of the positioning algorithm,this paper proposes an ultra-wideband positioning algorithm based on least squares(LS)and Taylor series(Taylor).Firstly,the least square method is used for rough positioning,then the coarse data is optimized by threshold filtering and weight calculation to obtain the best initial value,and finally the positioning point is iteratively solved by the Taylor algorithm to obtain accurate position coordinates.Simulation experiment results show that the positioning error of this method for fixed/mobile nodes is controlled at about 5 cm,which can meet most strict industrial application environments.
作者
陈磊
王菲菲
焦良葆
曹雪虹
Chen Lei;Wang Feifei;Jiao Liangbao;Cao Xuehong(School of Electric Pow er Engineering,Nanjing Institute of Technology,Nanjing 211167,China;Artificial Intelligence Industry Technology Research Center,Nanjing Institute of Technology Institute,Nanjing 211167,China)
出处
《信息化研究》
2020年第2期30-35,共6页
INFORMATIZATION RESEARCH
基金
国家自然科学基金(No.61703201)。
关键词
最小二乘
泰勒级数
阈值筛选
权重计算
least squares
Taylor series
threshold filtering
weight calculation
