Underwater Target Detection Using Single-Photon LiDAR Based on the Anglerfish's Lure-Based Hunting Mechanism

The search for sunken ships, aircraft wreckage, and other underwater debris, as well as conducting marine emergency rescue operations, are becoming increasingly significant. However, traditional detection methods suffer from limitations such as weak signal detection capability and low detection accuracy, which severely hinder the precise detection of underwater debris and the efficiency of emergency rescue operations. To address this issue, a biologically inspired hierarchical trapping mechanism is presented. By mimicking the trapping behavior of deep-sea anglerfish using bioluminescent lures, a 'global environment perception - local edge enhancement - dynamic strategy optimization' architecture is designed to improve the network's feature extraction capability. This is then combined with underwater single-photon LiDAR to achieve precise detection of underwater debris. The test results show that the presented method achieves an accuracy of 86.2% in identifying sunken ships and aircraft wreckage, representing a 29% improvement compared to traditional models trained with real-world data. This shows that the proposed method effectively addresses engineering challenges, including the high cost of acquiring underwater target-detection data, insufficient sample diversity, and low efficiency in underwater debris detection and emergency rescue operations.