为了解决雷达人工标绘耗时、难以数字化且非最优问题以及“试操船”功能依赖于操作人员主观调参以动态确定避碰方案的不确定性和非最优性且无法提供复航时机的问题，提出一种可行的多变量、单目标优化方法。基于雷达现有ARPA功能提供的目标运动要素及碰撞参数（DCPA和TCPA），以延迟时间、避让航向和时间、复航航向和时间为优化对象，以船舶绕航距离最短为优化目标，考虑避碰规则要求和基于标绘原理构建约束条件，建立雷达自动标绘功能优化模型，利用遗传算法完成模型求解并进行仿真实验验证。实验结果表明，建立的优化模型在对遇、交叉相遇和追越等局面下均可生成最优标绘避让方案。该方法建立了人工标绘原理的优化模型，实现自动试操船（即雷达全自动标绘）功能，可应用于雷达模拟器及真机，有效完善其依靠目标跟踪和试操船进行辅助避碰的功能，对使用雷达进行避碰操作具有一定的指导意义，同时可用于船舶避碰路径规划、辅助船舶自主避碰策略的制定。
In order to solve the problem that time-consuming、 difficult to digitalize and non-optimal for manual plotting with radar, and the uncertainty and non-optimality for the collision avoidance scheme determined by the operator's subjective parameter adjustment of the radar trial operation function, and can not provide the resumption of the route time, a feasible multi-variable and single-objective optimization method is proposed, Based on the target motion elements and collision parameters (DCPA and TCPA) provided by the existing ARPA function of radar, the method takes delay time, collision avoidance course and time, course and time of resumption as optimization objects, and the shortest deviation distance of ship as optimization objectives, considering the requirements of collision avoidance rules and based on the plotting principles to build constraint condition. Finally, the optimization model of radar automatic plotting function was established, and the model was solved by genetic algorithm and verified by simulation experiment. The experimental results show that the established optimized model can generate the optimal plot avoidance scheme under the situations of head-on, crossing and overtaking, etc. This method establishes the optimization model of manual plotting principle and realizes the function of automatic radar trial operation (i.e. automatic radar plotting), and can be applied to radar simulators and real radar machine to effectively improve the auxiliary collision avoidance function relying on target tracking and trial manoeuvre. It has certain guiding significance for the operation of collision avoidance with radar, and it can be used for ship collision avoidance path planning and assisting the development of ship autonomous collision avoidance strategy.
2024,46(21): 138-142 收稿日期：2023-12-26
DOI：10.3404/j.issn.1672-7649.2024.21.024
分类号：U666.1
基金项目：国家科技部资助项目（2021YFC2801004）；舟山市科技计划项目（2020C21024）
作者简介：梁民仓(1991-)男,博士,讲师,研究方向为船舶智能航行、航海仿真
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