A network-based approach on detecting dredgers’ illegal behavior of dumping dredged sediments

Focusing on detecting the illegal behavior of dumping dredged sediments by dredgers at ports, a sensor network composed of two acoustic sources and several passive sensor arrays is proposed in this article. The approach can be divided into two parts: the local sensor decision model and the fusion center algorithm. Local sensors receive signals emitted from the acoustic sources and extract the corresponding Hilbert–Huang marginal spectrum, which is significantly different between the scenario of illegal dumping dredged sediments and the contrary. Local decision is made based on spectrum feature extraction and classification. In regard to the fusion center, a fusion strategy with a scanning window is adopted to make a system-level decision. With a proper window width and the corresponding Bayes optimum threshold, the proposed approach performs well in simulations, in terms of a low system-level false alarm probability and a low system-level miss alarm probability.

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