大雾天气显著降低了能见度，使得激光雷达信号受到严重干扰，难以准确提取船舶信号变得困难。同时，船舶的动态变化导致边界识别困难，导致船舶碰撞风险识别精度较低。因此，提出大雾天气船舶碰撞风险激光雷达识别算法设计。在大雾天气条件下，对激光雷达信号预处理，得到高精度船舶信号，对得到的船舶信号数据基于尺寸信息执行边界运算，以获取船舶边界数据以及靠近速度，并以此作为船舶碰撞风险识别指标。依据隶属函数，结合风险识别指标建立判断矩阵，通过碰撞危险度量化，归一化处理及去模糊化运算，得出船舶碰撞风险等级。依据平均碰撞风险识别目标船舶整个航程的风险等级。实验结果表明，该算法对船舶碰撞风险识别精度高，整体性能强。
The foggy weather significantly reduces the visibility, which makes the lidar signal severely disturbed, and it is difficult to accurately extract the ship signal. At the same time, the dynamic change of ship leads to the difficulty of boundary identification, resulting in the low accuracy of ship collision risk identification. Therefore, the design of liDAR identification algorithm for ship collision risk in foggy weather is proposed. In foggy weather conditions, the laser radar signal is pre-processed to obtain high-precision ship signals, and the ship signal data is obtained by boundary calculation based on the size information to obtain ship boundary data and approach speed, which is used as the identification index of ship collision risk. According to the membership function and risk identification index, the judgment matrix is established, and the collision risk level is obtained through the quantification, normalization and defuzzification of collision risk. Identify the risk level of the target ship throughout the voyage based on the average collision risk. Experimental results show that the algorithm has high accuracy and strong overall performance for ship collision risk identification.
2024,46(18): 138-142 收稿日期：2024-3-4
DOI：10.3404/j.issn.1672-7649.2024.18.024
分类号：U698.2
基金项目：中央引导地方科技发展资金项目（YDZJ2022022）
作者简介：李鹏展(1971-),男,高级工程师,研究方向为船舶与海洋装备管理
参考文献：
[1] 田国红, 关亮亮. 无人驾驶车前方不确定障碍物检测方法仿真[J]. 计算机仿真, 2023, 40(2): 471-474+481.
[2] 霍健, 陈慧敏, 马云飞, 等. 基于MEMS激光雷达的车辆目标识别算法[J]. 兵工学报, 2023, 44(4): 940-948.
[3] 李昀哲, 王硕丰, 刘彬, 等. 基于深度强化学习的船舶避碰决策算法[J]. 船舶工程, 2022, 44(10): 118-126.
[4] 张照亿, 李颖, 董双, 等. 基于船舶领域模型的船舶碰撞危险识别方法[J]. 中国航海, 2021, 44(2): 1-7+14.
[5] 张金奋, 游斌, 蔡明佑, 等. AIS数据驱动下的渡船横越场景识别与碰撞风险建模[J]. 中国航海, 2023, 46(2): 46-53+59.
[6] YU Q , TEIXEIRA A P , LIU K , et al. Framework and application of multi-criteria ship collision risk assessment[J]. Ocean engineering, 2022, 250(Apr. 15): 111006.1-111006.17.
[7] 邢星宇, 黄安, 姜为, 等. 降雨条件下车载激光雷达感知局限性[J]. 同济大学学报(自然科学版), 2023, 51(5): 785-793.
[8] 罗雄, 史悦, 范琪, 等. 基于相干激光雷达气象多要素探测[J]. 红外与激光工程, 2023, 52(11): 67-76.
