Hierarchical copula-based distributed detection

Abstract Detection is one of the main tasks of wireless sensor networks (WSN) in many applications. The data of network nodes are usually assumed to be statistically independent since considering dependence results in intractable decision rules. However, detection performance degrades when the correlation rises. In this paper, a practically popular configuration of WSNs is considered where homogeneous nodes - each of them consisting of several heterogeneous sensors - send their processed data to a fusion center (FC). Here, data fusion should be implemented in two levels: 1. Nodes fuse the data of their sensors. 2. The FC takes the final decision by fusing the data of the nodes. We propose to implement a copula-based local decision rule in nodes. At the FC, it is shown that the correlation among nodes’ decisions can be resolved by simply adding the logarithm of the sum of nodes’ decisions to the statistic of the FC. The proposed distributed detection scheme is evaluated in a practical example of fire detection. Simulations show that considering correlation by implementing the proposed methods would improve detection performance.

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