A ship target detection method based on LiDAR under inland waterways

Accurate waterway flow monitoring plays an important role in improving ship-shore coordination and promoting the construction of smart waterways. However, traditional methods, including video surveillance and infrared detectors, are susceptible to light and temperature, making it difficult to obtain accurate waterway flow monitoring results. In contrast, the LiDAR sensor is not sensitive to changes in external light and has strong adaptability to complex environments. It can realize real-time and accurate monitoring of waterway traffic. In order to realize ship target detection to obtain accurate waterway flow, we first designed a real-time 3D point cloud background filtering algorithm based on the intensity values of the background point cloud to efficiently acquire ship point cloud data and reduce the data volume. After that, we design a laser beam-based ship target detection algorithm based on the ship's point cloud features, which utilizes the characteristics of the existence time of ship point cloud on the detection cross-section and the edge characteristics of bow and stern, and the change characteristics of the point cloud on the detection cross-section. We validate the accuracy of the proposed method by ships data collected in real scenarios, and the results show that the accuracy reaches 96.3%.