分类： 交通运输工程 >> 水路运输 提交时间： 2024-03-31
摘要： The ship motion perception approaches mainly use maritime radar, Automatic Identification System (AIS) and cameras. However, using either of these approaches alone may result in information inconsistency and insufficient data accuracy. Therefore, a multi-sensor fusion perception system is proposed in this study to monitor ship motion in inland waterways. Firstly, a hardware platform of multi-sensor fusion ship motion perception system composed of maritime radar, AIS, cameras and other accessories is constructed. Secondly, by utilizing the target detection and tracking algorithms, track association algorithms, the ship motion data collected from the three sensors are integrated. Finally, the performance of the ship motion perception system is verified by field experiments in day and night. The experimental results indicate that the integrated ship motion perception system with multiple sensors is able to improve the information consistency and data accuracy of ship motion apparently in inland waterway compared to other perception systems.
分类： 交通运输工程 >> 水路运输 提交时间： 2024-03-28
摘要： Vessel recognition plays important role in ensuring navigation safety. However, existing methods are mainly based on a single sensor, such as automatic identification system (AIS), marine radar, closed-circuit television (CCTV), etc. To this end, this paper proposes a coarse-to-fine recognition method by fusing CCTV and marine radar, called multi-scale matching vessel recognition (MSM-VR). This method first proposes a novel calibration method that does not use any additional calibration target. The calibration is transformed to solve an N point registration model. Furthermore, marine radar image is used for coarse detection. A region of interest (ROI) area is computed for coarse detection results. Lastly, we design a novel convolutional neural network (CNN) called VesNet and transform the recognition into feature extraction. The VesNet is used to extract the vessel features. As a result, the MVM-VR method has been validated by using actual datasets collected along different waterways such as Nanjing waterway and Wuhan waterway, China, covering different times and weather conditions. Experimental results show that the MSM-VR method can adapt to different times, different weather conditions, and different waterways with good detection stability. The recognition accuracy is no less than 96%. Compared to other methods, the proposed method has high accuracy and great robustness.
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