Abstract
Piracy has posed intractable challenges to maritime security and the global economy. This study introduces a real-time early warning system designed to monitor piracy activity in the vicinity of merchant vessels, thereby facilitating the assessment and countermeasure of potential attacks. The approach employs frequency agile radar to identify pirate ships characterized by aggregation and jamming behavior. To address the computational difficulties caused by changing frequencies, compressed sensing with a tailored target information processing procedure is applied to reconstruct the radar observation scene. The developed target detection algorithm yields precise information about nearby pirate ships, enabling a comprehensive evaluation of the risk level and the subsequent recommendation of an appropriate security scheme. Extensive experiments have shown that the proposed early warning model can provide best warning performance compared to other benchmark models, with an average accuracy of 0.964, precision of 0.966, recall of 0.955, F1 score of 0.960.
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