系统仿真学报 ›› 2023, Vol. 35 ›› Issue (9): 1909-1917.doi: 10.16182/j.issn1004731x.joss.22-0556

• 论文 • 上一篇    下一篇

特定多任务下飞机航迹规划研究

钟麟1(), 佟明安2, 李盛1   

  1. 1.西京学院 电子信息学院,陕西 西安 710123
    2.西北工业大学 电子信息学院,陕西 西安 710072
  • 收稿日期:2022-05-25 修回日期:2022-07-08 出版日期:2023-09-25 发布日期:2023-09-19
  • 第一作者简介:钟麟(1975-),男,副教授,博士,研究方向为复杂系统建模等。E-mail:zhong_chen2@163.com
  • 基金资助:
    国家自然科学基金(11974289)

Research on Flight Route Planning for Specific Multi-missions

Zhong Lin1(), Tong Ming'an2, Li Sheng1   

  1. 1.College of Electronic Information, Xijing University, Xi'an 710123, China
    2.College of Electronic Information, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2022-05-25 Revised:2022-07-08 Online:2023-09-25 Published:2023-09-19

摘要:

为了更好地完成航空特定任务,提出了特定多任务下飞机航迹规划模型。采用栅格法建立战场环境模型,根据复杂、真实战场环境以及作战要求,提出了距离、油耗、任务完成度、地对空威胁和空对空威胁5个目标航迹规划的模型。根据特定任务的要求,分析了满足任务的各种需求,给出了评估任务完成度指标。根据该问题的特点,提出一种两阶段的航迹规划求解算法。第一个阶段用简化二维路径规划模型计算多任务顺序,第二阶段根据多任务顺序使用改进A*算法求解多目标栅格优化问题,解决了A*算法不能处理时变优化问题情况。仿真结果表明该方法能很好地解决多任务、多目标航迹规划问题,比目前的算法更高效。

关键词: 任务航迹规划, 多目标优化, 任务需求, 威胁

Abstract:

In order to complete specific aviation missions, a flight route planning model for specific multi-missions is presented. The grid method is used to build a battlefield environment model. According to the complex and real battlefield environment and operational requirements, five target route planning models including distance, fuel consumption, mission completion, ground-to-air threat, and air-to-air threat are proposed. On the basis of specific mission demands, several requirements for missions are analyzed, and the index of mission completion is presented. According to the problem's characteristics, the two-stage solution algorithm for route planning is proposed. In the first stage, the multi-mission sequence is calculated by simplifying a two-dimensional route planning model. In the second stage, the modified A* algorithm is used to solve the multi-target grid optimization problem according to the multi-mission sequence, and the failureof the A* algorithm to handle time-varying optimization is solved. The simulation results show the method can manage multi-mission and multi-target route planning more effectively than the present algorithms.

Key words: mission route planning, multi-target optimization, mission demand, threat

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