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Multiple target localization in WSNs using compressed sensing reconstruction based on ABC algorithm

机译:基于ABC算法的压缩感知重建在无线传感器网络中的多目标定位。

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In allusion to the application of compressed sensing theory in multi-target localization in wireless sensor networks, the paper proposes a method of sparse signal reconstruction based on artificial bee colony algorithm and designs partial update strategy of location coding. A mode of disturbances mutation operation for food source exploitation is designed to improve the search efficiency in high-dimensional solution space; it also improves the global search efficiency of the algorithm. The comparing of simulation analysis with other algorithms verifies that the algorithm effectively solves problem of multi-target localization in wireless sensor networks and has better resistance to interference.
机译:针对压缩感知理论在无线传感器网络多目标定位中的应用,提出了一种基于人工蜂群算法的稀疏信号重构方法,并设计了位置编码的局部更新策略。设计了一种用于食物源开发的扰动变异操作模式,以提高高维解空间中的搜索效率。它还提高了算法的全局搜索效率。仿真分析与其他算法的比较表明,该算法有效解决了无线传感器网络中的多目标定位问题,具有较好的抗干扰能力。

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