为全面展示船舶航行环境以及船舶航迹，保障船舶在航行时的安全以及稳定性，提出基于信息交互与传达技术的船舶航迹界面设计方法。硬件设计中，利用信息交互与传达技术设计船舶航迹界面架构。利用B/S架构以及ZigBee开发机制设计信息交互平台。使用隶属视觉传达技术搭建船舶航迹图形界面。控制显示模块视觉传达功能中设计了电子海图显示、船舶航迹管理等功能。软件设计中，利用信息感知技术从海图作业功能模块中抽取相应的海图数据，并采集船舶航行环境信息，以抽取海图数据以及所获船舶航行环境信息为可靠依据，利用改进蚁群算法规划船舶航迹，利用中值滤波方法滤除轨迹图像噪声，可视化呈现船舶航行环境以及航行轨迹。结果表明，应用该方法能够设计出效果较好的船舶航迹界面，收获更为理想的船舶航行效果。
In order to comprehensively demonstrate the navigation environment and trajectory of ships, and ensure the safety and stability of ships during navigation, a design method for ship trajectory interface based on information exchange and communication technology is proposed. In hardware design, the architecture of ship trajectory interface is designed using information exchange and communication technology. Design an information exchange platform using the B/S architecture and ZigBee development mechanism. Using subordinate visual communication technology to build a graphical interface for ship trajectory. The visual communication function of the control display module includes electronic chart display, ship trajectory management, and other functions. In software design, information perception technology is used to extract corresponding chart data from the chart operation function module and collect ship navigation environment information. Based on the extracted chart data and the obtained ship navigation environment information as a reliable basis, improved ant colony algorithm is used to plan the ship's trajectory, and median filtering method is used to filter out trajectory image noise, visualizing the ship's navigation environment and trajectory. The experimental results show that the application of this method can design a ship trajectory interface with better results, and achieve more ideal ship navigation effects.
2023,45(20): 198-201 收稿日期：2023-4-18
DOI：10.3404/j.issn.1672-7649.2023.20.038
分类号：TB472
作者简介：朱丹(1989-),女,硕士,讲师,研究方向为视觉传达设计
参考文献：
[1] 牛雯钰, 梁茂晗, 刘文, 等. 多特征点驱动的船舶轨迹聚类方法[J]. 交通信息与安全, 2023, 41(1): 62-74.
[2] 蒋通, 崔良中, 刘立国, 等. 基于聚类分析和Att-Bi-LSTM的舰船航迹预测方法[J]. 计算机仿真, 2022, 39(8): 1-5+322.
[3] 侯岳奇, 陶浩, 龚俊斌, 等. 多约束条件下无人艇和无人机集群协同航迹规划[J]. 中国舰船研究, 2021, 16(1): 74-82.
[4] 吴潇灿, 孙冬梅, 赵航, 等. 基于NARX神经网络的组合导航系统设计[J]. 电子器件, 2020, 43(1): 215-219.
[5] 古毅杰, 张闯, 房美含. 基于输入延迟神经网络的船舶GPS/INS组合导航[J]. 船舶工程, 2022, 44(7): 96-102.
[6] 刘娣, 陈桂, 朱松青. 基于多接收机的卫星/惯性组合导航系统研究[J]. 现代雷达, 2021, 43(12): 39-44.
[7] 王星宇, 胡燕海, 徐坚磊, 等. 基于改进蚁群算法的机器人路径规划方法[J]. 电子技术应用, 2023, 49(1): 75-80.
[8] 黄国良, 周毅, 郑坤, 等. 基于改进蚁群算法的全局船舶路径规划方法[J]. 船海工程, 2023, 52(2): 97-101, 136.
