多跳无线传感器网络下信道感知的目标定位方法

针对资源有限、存在信道退化的无线传感器网络(Wireless sensor network, WSN),基于最大似然估计(Maximum-likelihood estimation, MLE)提出一种信道感知的目标定位方法. 把传感器观测数据量化为M位二进制序列,经过衰落信道多跳中继到达融合中心. 中继节点采用二元解码-前向中继策略,中继输出是被信道污染的中继信号的估计值. 在Rayleigh信道衰落和高斯信道噪声假设下,结合无线信道衰落的统计知识和解码策略, 推导了观测数据的似然函数,得到目标位置的最大似然估计. 此外,还推导了估计器性能的后验克拉美-罗下界(Cramr-Rao lower bounds, CRLB). 仿真结果表明,信道感知的方法能够减缓由于信道衰落和噪声所带来的定位性能的退化.

Channel Aware Target Localization in Multi-hop Wireless Sensor Networks

In this paper, a novel channel aware target localization approach is proposed for channel-faded and resource-constrained wireless sensor network (WSN) based on maximum-likelihood estimation (MLE). The measurements from local sensor are quantized and coded to an M-bit data, then relayed through multi-hop fading channels to reach a fusion center. Each relay node employs a binary decode-and-forward relay scheme where the relay output is inferred from the channel impaired observation received from its source node. The observation likelihood function is derived which incorporates wireless channel statistics as well as decoding scheme characteristics. The target location is estimated based on maximum-likelihood method. Furthermore, we derive the Cramér-Rao lower bound (CRLB) for our proposed channel-aware localization method. Simulation results are presented to show that the channel-aware approach can mitigate the performance degradation caused by the channel imperfection.