摘要
在对定位算法中的测距和非测距算法研究的基础上,本文提出了在改进阅读器排布的定位空间中,将最近邻居算法与Chan算法结合,进行协同定位的方法。在设定的两种小范围仿真空间中,通过均方误差(RMSE)和误差累计分布曲线(CDF)两个定位精度评价指标对改进前后的算法进行比较,在噪声较小且误差均匀分布的环境下,改进算法的定位误差可90%控制在0.4m以内。
After a researching of positioning algorithm including ranging-free and ranging-based algorithm,a synthesis algorithm named KN-CHAN is proposed,which combines K-nearest neighbor algorithm with Chan algorithm in a reader-rearranged location space.The synthesis algorithm was compared under two evaluating indicator(RMSE and CDF) with several other algorithms such as KN,Chan,KN-Taylor in the two designed simulation environments with small area,whose RMSE(root-mean-square error) can be controlled at 90% less than 0.4m in the situation of low-intensity and evenly-distributed noise.
出处
《无线通信技术》
2012年第3期8-11,15,共5页
Wireless Communication Technology
基金
中央高校基本科研业务费专项资金项目资助(项目编号:2011JS148)
关键词
最近邻居算法
Chan氏算法
算法融合
K-nearest neighbor algorithm
Chan algorithm
integration algorithm
