In this letter, we study data-aided sensing (DAS) for distributed detection in wireless sensor networks (WSNs) when sensors’ measurements are correlated. In particular, we derive a node selection criterion based on the J-divergence in DAS for reliable decision subject to a decision delay constraint. Based on the proposed J-divergence based DAS, the nodes can be selected to rapidly increase the log-likelihood ratio (LLR), which leads to a reliable decision with a smaller number of the sensors that upload measurements for a shorter decision delay. From simulation results, it is confirmed that the J-divergence based DAS can provide a reliable decision with a smaller number of sensors compared to other approaches.

中文翻译：

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分布式检测的数据辅助传感

在这封信中，我们研究了当传感器的测量值相关时在无线传感器网络（WSN）中进行分布式检测的数据辅助传感（DAS）。特别是，我们基于DAS中的J-散度推导节点选择标准，以进行受决策延迟约束的可靠决策。基于提出的基于J散度的DAS，可以选择节点以快速增加对数似然比（LLR），从而使用较少数量的传感器上传更短决策延迟的传感器即可得出可靠的决策。从仿真结果可以证实，与其他方法相比，基于J散度的DAS可以使用更少的传感器来提供可靠的决策。