The critical speeds and radii for converage in sensor networks注意:本论文已在《the 2007 International Conference on Intelligent Computing (ICIC 2007)》发表 Abstract: It is well known that localization plays an important
role in wireless sensor network applications. There are
two categories of localization approaches, such as
range-based and range-free. RSSI(Received Signal
Strength Indicator)-based method is in the first category.
Three RSSI-based distance estimators, Biased
Estimator (BE), Unbiased Estimator (UE) and Maximal
Likelihood Estimator (MLE), are presented to calculate
the distance. The biased estimator is the existing method
which is used extensively in the literatures, while the
unbiased estimator and maximal likelihood estimator
are two new estimators developed in this paper. The
probabilistic analysis of those estimators is done to
compare the performance among them. The
probabilistic analysis and simulations show that under
some condition we should choose unbiased estimator
and under some other condition we should choose MLE. 1、浏览PDF格式全文需要使用软件--Abode Acrobat(由于软件较大并常见,我站不提供下载) 2、下载论文全文请点击鼠标右键“另存为”或使用断点续传软件下载(857KB) 本站收录的本文作者的其他论文: 1、基于多智能体理论实现无线传感器网络的目标监视与追踪的策略 4、Target Tracking based on the Dynamic Cluster Method in the Acoustic Sensor Network 6、The Probabilistic Analysis of Distance Estimators in Wireless Sensor Network
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