%0 Journal Article
%T Using steepest descent method to improve node localization accuracy of maximum likelihood estimation<br>使用最速下降算法提高极大似然估计算法的节点定位精度*
%A SHI Qin-qin
%A HUO Hong
%A FANG Tao
%A LI De-ren
%A <br>石琴琴
%A 霍宏
%A 方涛
%A 李德仁
%J 计算机应用研究
%D 2008
%I 
%X This paper expounded the localization principle of maximum likelihood estimation.Also, presented the principle of using steepest descent method to find an optimal solution for a system of nonlinear equations.Proposed steepest descent method to refine the initial node locations gotten by maximum likelihood estimation as the distance measurement error was large, and corresponding simulation experiment was done to testify the validity and advantages of such a disposal. The simulation results show that the refinement can improve the localization accuracy obviously with no more communication cost and small computation cost, fit to be utilized in wireless sensor networks.
%K wireless sensor network
%K node localization
%K maximum likelihood estimation
%K steepest descent method<br>无线传感器网络
%K 节点自定位
%K 极大似然估计算法
%K 最速下降算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=0925A12792124004202AAB71F1AF8D83&yid=67289AFF6305E306&vid=C5154311167311FE&iid=DF92D298D3FF1E6E&sid=438F607B4D053FEF&eid=2D8A2D26AFF207D2&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12