Sensor Selection for Target Tracking in Wireless Sensor Networks With Uncertainty
Sensor Selection for Target Tracking in Wireless Sensor Networks With Uncertainty
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DOI：
10.1109/tsp.2016.2595500
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发表时间：
2016-10-15
影响因子：
5.4
通讯作者：
Varshney, Pramod K.
中科院分区：
文献类型：
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作者：
Cao, Nianxia;Choi, Sora;Varshney, Pramod K.
针对不确定无线传感器网络(WSNs)中的传感器选择问题，提出了一个多目标优化框架。无线传感器网络的不确定性导致了一组关于目标信息不足的传感器观测。提出了一种新的基于互信息上界(MIUB)的传感器选择方案，该方案的计算复杂度与基于Fisher信息(FI)的传感器选择方案相同，并给出了与基于互信息的传感器选择方案相似的估计性能。多目标优化问题(MOP)在不事先知道要选择的传感器数量的情况下，给出了一组传感器选择策略，这些策略揭示了两个相互冲突的目标之间的不同权衡：当所有传感器都传输测量数据时，最小化所选传感器的数量，并且最小化性能指标(MIUB和FI)之间的差距；当基于传感器选择策略，仅当所选传感器传输其测量数据时。文中给出了提供有价值见解的说明性数值结果。
In this paper, we propose a multiobjective optimization framework for the sensor selection problem in uncertain Wireless Sensor Networks (WSNs). The uncertainties of the WSNs result in a set of sensor observations with insufficient information about the target. We propose a novel mutual information upper bound (MIUB)-based sensor selection scheme, which has a low computational complexity, same as the Fisher information (FI)-based sensor selection scheme, and gives an estimation performance similar to the mutual information-based sensor selection scheme. Without knowing the number of sensors to be selected a priori, the multiobjective optimization problem (MOP) gives a set of sensor selection strategies that reveal different tradeoffs between two conflicting objectives: minimization of the number of selected sensors and minimization of the gap between the performance metric (MIUB and FI) when all the sensors transmit measurements and when only the selected sensors transmit their measurements based on the sensor selection strategy. Illustrative numerical results that provide valuable insights are presented.