Passive location estimation using scatterer information for non-line-of-sight environments  

非视距环境下基于散射体信息的被动定位(英文)

作　　者：颜俊[1] 王林汝[1] 吴乐南[1] 

机构地区：[1]东南大学信息科学与工程学院,南京210096

出　　处：《Journal of Southeast University(English Edition)》2010年第4期518-522,共5页东南大学学报（英文版）

基　　金：The National High Technology Research and Development Program of China(863Program)(No.2008AA01Z227);the National Natural Science Foundation of China(No.60872075)

摘　　要：In order to improve the performance of the traditional hybrid time-of-arrival（TOA）/angle-of-arrival（AOA）location algorithm in non-line-of-sight（NLOS）environments,a new hybrid TOA/AOA location estimation algorithm by utilizing scatterer information is proposed.The linearized region of the mobile station（MS）is obtained according to the base station（BS）coordinates and the TOA measurements.The candidate points（CPs）of the MS are generated from this region.Then,using the measured TOA and AOA measurements,the radius of each scatterer is computed.Compared with the prior scatterer information,true CPs are obtained among all the CPs.The adaptive fuzzy clustering（AFC）technology is adopted to estimate the position of the MS with true CPs.Finally,simulations are conducted to evaluate the performance of the algorithm.The results demonstrate that the proposed location algorithm can significantly mitigate the NLOS effect and efficiently estimate the MS position.为了提高传统的TOA/AOA定位技术在非视距环境下的定位精度,提出了一种基于散射体信息的混合定位方法.首先,利用基站坐标信息和TOA测量值确定线性化的可行区域,产生移动台的候选位置点.对每一个移动台候选点,结合TOA和AOA测量值,计算各自散射体半径,通过与先验的散射体信息的比较,筛选候选移动台位置点.然后,运用自适应模糊聚类算法估计移动台位置,完成定位.最后,对所提出的定位算法进行了仿真验证.仿真结果表明:所提出的基于散射体信息的混合TOA/AOA定位算法能够减轻非视距效应,有效估计移动台位置.

关 键 词：passive location time-of-arrival/angle-of-arrival（TOA/AOA） non-line-of-sight（NLOS）mitigation adaptive fuzzy clustering 

分 类 号：TN911.7[电子电信—通信与信息系统]