%0 Journal Article
%T A TOA/ AOA Location Algorithm in NLOS Environment<br>一种NLOS环境下的TOA/AOA定位算法
%A Mao Yong-yi
%A Li Ming-yuan
%A Zhang Bao-jun
%A <br>毛永毅
%A 李明远
%A 张宝军
%J 电子与信息学报
%D 2009
%I 
%X In order to mitigate the effect of NLOS propagation, based on the Geometry Based Single- Bounced (GBSB)statistical model, a TOA/AOA location algorithm based on the RBF neural network is proposed. The fast study and non-linear approach capacity of the neural network is made use of to correct the error of NLOS propagation, then the position is calculated by Least-Square (LS) algorithm to improve the location0] accuracy. The simulation results indicate that the location accuracy is significantly improved and the performance of this algorithm is better than that of Chan algorithm, Taylor algorithm and LS algorithm in NLOS environment.
%K Location algorithm
%K TOA
%K AOA
%K NLOS
%K LS algorithm
%K Neural network<br>定位算法
%K 波达时间
%K 电波到达角
%K 非视距传播
%K 最小二乘法
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=901F0457AFB4A708A253066E142D60CB&yid=DE12191FBD62783C&vid=4AD960B5AD2D111A&iid=CA4FD0336C81A37A&sid=42425781F0B1C26E&eid=1371F55DA51B6E64&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=5&reference_num=11