为避免复杂海洋环境下船舶航行碰撞问题，保障航行安全，设计卡尔曼滤波的船舶航行安全智能预警系统。系统通过船舶AIS电文信息处理模块深入处理从船站、岸站接收到的AIS电文信息，并将其压缩、存储至船舶信息数据库；船舶航行轨迹预测模块调用数据库中的船舶信息，采用信息化处理技术中的多项式卡尔曼滤波算法预测船舶动态轨迹；船舶航行安全智能预警模块依据船舶位置信息评估船舶航行风险，依据综合碰撞危险度划分预警等级，并设置分级预警机制保障航行安全。实验结果显示，该系统可以准确轨舶航行轨迹；并会遇到船舶和暗礁等障碍物时，准确发出预警，预警等级合理，船员可根据不同预警做出有效避撞操作，且安全气囊在达到预设条件时及时启动，分级预警具备安全防护可靠性。
To avoid ship navigation collisions in complex marine environments and ensure navigation safety, a Kalman filter based intelligent warning system for ship navigation safety is designed. The system deeply processes the AIS message information received from the ship station and shore station through the ship AIS message information processing module, and compresses and stores it in the ship information database; The ship navigation trajectory prediction module calls the ship information in the database and uses the polynomial Kalman filter algorithm in information processing technology to predict the dynamic trajectory of the ship; The intelligent warning module for ship navigation safety evaluates ship navigation risks based on ship location information, divides warning levels based on comprehensive collision risk, and sets up a graded warning mechanism to ensure navigation safety. The experimental results show that the system can accurately track the navigation trajectory of ships; And when encountering obstacles such as ships and reefs, accurate warnings should be issued with reasonable warning levels. Crew members can make effective collision avoidance operations based on different warnings, and the safety airbags should be activated in a timely manner when the preset conditions are met. The graded warnings have reliable safety protection.
2025,47(13): 167-171 收稿日期：2025-6-10
DOI：10.3404/j.issn.1672-7649.2025.13.029
分类号：U675.96
基金项目：中国博士后基金面上项目（2017M612541）；武汉船舶职业技术学院2025年院级课题（2025Z07）
作者简介：刘珩(1990-),女,硕士,讲师,研究方向为数字传播
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