无线传感器网络中目标定位的信道感知自适应量化

Guiyun Liu, Hua Liu, Hongbin Chen, Jianhua Xiang, Zhong Xiao
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引用次数: 1

摘要

研究了无线传感器网络中源定位的量化方案问题。首先,提出了一种信道感知的目标位置估计自适应量化方案,局部传感器节点根据一种基于位置的信息序列动态调整量化阈值;该方案结合了传感器与融合中心之间不完美无线信道的统计特性。在此基础上,推导了合适的最大似然估计量(MLE)和性能度量cram - rao下界(CRLB)。仿真结果表明,所提出的最大似然值小于固定量化信道感知的最大似然值,当传感器数量足够大时,所提出的最大似然值将接近其最大似然值。
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Channel aware adaptive quantization for target localization in wireless sensor networks
This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme incorporates the statistics of imperfect wireless channels between sensors and the fusion center. Furthermore, the appropriate maximum likelihood estimator (MLE) and the performance metric Cramér-Rao lower bound (CRLB) are derived. Simulation results are presented to show that the appropriated CRLB is less than the fixed-quantization channel-aware CRLB and the proposed MLE will approach its CRLB when the number of sensors is large enough.
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