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The Probabilistic Analysis of Distance Estimators in Wireless Sensor Network

注意:本論文已在《Proceedings of the Third International Conference on Natural Computation 》(ICNC 2007) - Volume 05,270-275發表
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ZANG Chuan-zhi  LIANG Wei  YU Hai-bin
(Shenyang Institute Automation,Chinese Academy of Sciences,Shenyang 110016)

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.

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本站收錄的本文作者的其他論文:

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2、無線傳感器網絡中基于移動智能體的目標追蹤

3、無線傳感器網絡覆蓋問題中的目標最優運動模式

4、Target Tracking based on the Dynamic Cluster Method in the Acoustic Sensor Network

5、無線傳感器網絡動態協同任務分配機制

6、THE PROBABILISTIC ANALYSIS OF RSSI-BASED DISTANCE ESTIMATORS IN WIRELESS SENSOR NETWORK

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