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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.
In order to solve the problem of signal source detection in the area monitored by wireless sensor networks, a LEACH (Low Energy Consolidated Clustering Hierarchical Protocol) algorithm and Bayesian Compressive Sensing (CS) method are proposed. The LEACH algorithm clusters the network nodes and selects the cluster heads, concentrating the nodes’ information in the clusters on the cluster heads and transmitting the information to the aggregation nodes only through the cluster heads, so as to reduce the number of nodes that transmit data to the aggregation nodes. The Bayesian CS algorithm can recover the signal source from a small amount of data from the cluster head, and at the same time, a threshold mechanism is proposed to optimize the signal reconstruction performance of the CS algorithm when the data volume is too small. The simulation results show that, The algorithm can detect the target accurately and has better performance.