摘要
针对信道退化的多跳无线传感器网络下的定位问题,基于最大似然估计提出一种新的信道容错的定位算法.传感器节点接收到的源信号强度数据被压缩量化为二元信号,经Rayleigh退化信道多跳中继到达融合中心.利用信道退化统计量和译码策略,推导出二元观测数据的似然函数,基于最大似然估计获得目标定位,进一步给出目标位置估计的克拉美-罗下界.仿真结果表明了所提出算法的有效性.
A novel channel fault-tolerant localization algorithm based on maximum-likelihood estimation is proposed for localization in a multi-hop wireless sensor networks with channel fading. The received measurement of source signal energy from local sensors is compressed and quantized into binary data and transmitted to the fusion center via multi-hop Rayleigh fading channels. The likelihood function of binary observation is derived by using wireless channel statistics and decoding scheme. The localization of target is achieved by maximum-likelihood estimation. Furthermore, the Cramer-Rao lower bounds for the estimates are derived. Simulation results show the effectiveness of the proposed algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2014年第4期739-742,共4页
Control and Decision
基金
国家自然科学基金项目(60975028)
中国博士后科学基金项目(2013M540725)
陕西省科技攻关计划项目(2011K06-21)
中央高校基本科研业务费专项基金项目(2013G3242008)
关键词
目标定位
无线传感器网络
无线信道容错
克拉美一罗下界
target localization
wireless sensor networks
wireless channel fault-tolerant
Cramer-Rao lower bounds
