Cluster-head Election Algorithms in Fuzzy Logic Systems for Radar Sensor Networks
首发时间:2015-12-02
Abstract:In this paper, we propose three cluster-head election schemes using fuzzy logic systems (FLSs) for clustered radar sensor networks. Three factors of a radar sensor (RS) are considered in our FLS design: its remaining energy (RE); the fading envelope of the signal transmitted by the RS to base station (FESTRBS); its distance to base station (DBS). The three cluster-head election schemes are named FF (FLS with two-antecedents & fuzzy-c means (FCM) ), FFSVD (FLS with two-antecedents, FCM, and singular value decomposition-QR (SVD-QR)), and FF3SVD (FLS with three-antecedent FLS, FCM and SVD-QR). Their clustering performances in terms of detection performances and networks' lifetime are compared and analyzed. Monte Carlo simulations show that among these three cluster-head election schemes, FF3SVD provides the lowest energy consumption and moderate probability of target detection (PD), and FFSVD offers moderate power loss and the highest PD, whereas FF has the worst clustering performances.
keywords: signal and information processing, cluster-head election, fuzzy logic, radar sensor networks.
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基于模糊逻辑系统的雷达传感网簇头选择算法
摘要:本文提出了三种基于模糊逻辑系统的雷达传感网簇头选择算法,旨在提高网络检测性能的同时延长网络的生命周期。 在设计模糊逻辑系统时考虑的雷达传感器的因素有:雷达传感器的剩余能量、由雷达传感器向基站发送的信号的衰减包络以及雷达传感器与基站之间的距离。这三种簇头选择算法分别为FF(包括有两个输入的模糊逻辑系统和模糊c均值算法),FFSVD(包括有两个输入的模糊逻辑系统、模糊c均值算法以及奇异值分解算法)和FF3SVD(包括有三个输入的模糊逻辑系统、模糊c均值算法以及奇异值分解算法)。这三种算法的网络性能(包络网络的检测概率和网络能耗)由蒙特卡罗仿真给出。结果表明FF3SVD可提供最低的网络能耗和中等的目标检测概率,FFSVD具有最高的检测概率和中等的网络能耗,然而FF具有最差的网络性能。
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