基于LEACH和压缩感知的无线传感器网络目标探测

Source Detection in Wireless Sensor Network by LEACH and Compressive Sensing

为了解决在无线传感器网络监测的区域内进行信号目标源探测的问题,提出了一种联合低功耗自适应集簇分层型协议(LEACH)算法和贝叶斯压缩感知(CS)的方法.LEACH算法对网络节点进行分簇并选择簇头,将簇内节点的信息集中在簇头上,同时仅通过簇头向汇聚节点传递信息,可减少向汇聚节点传输数据的节点数.汇聚节点利用贝叶斯CS算法可从来自簇头的少量数据中恢复出信号源.同时提出了一种阈值机制,以优化在数据量过少情况下CS算法的信号重构性能.仿真结果表明,所提算法能对目标进行准确探测,具有较好的性能.

For study of the source detection areas monitored by wireless sensor network, an algorithm combining low energy adaptive clustering hierarchy（LEACH） algorithm and Bayesian compressive sensing （CS）is proposed. LEACH algorithm divides the sensors into some clusters and chooses the clusterheads. The information in the sensors is collected by the clusterheads. Only the clusterheads are allowed to transmit information to the fusion center. It reduces the number of sensors which send the information to the fusion center. The fusion center utilizes Bayesian CS to recover the source from a little measurement transmitted by clusterheads. At the same time, a threshold is set to optimize the performance of reconstruction when the data volume becomes little. Simulations show that the algorithm proposed can detect the source accurately, and obtain the good performance.