系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (9): 2912-2921.doi: 10.12305/j.issn.1001-506X.2023.09.31

• 制导、导航与控制 • 上一篇    下一篇

基于速度预测的防空导弹中制导末段协同弹道规划方法

崔正达1,*, 魏明英1,2, 李运迁1   

  1. 1. 北京电子工程总体研究所, 北京 100854
    2. 北京仿真中心, 北京 100854
  • 收稿日期:2022-07-07 出版日期:2023-08-30 发布日期:2023-09-05
  • 通讯作者: 崔正达
  • 作者简介:崔正达(1996—), 男, 博士研究生, 主要研究方向为导航、制导与控制
    魏明英(1966—), 女, 研究员, 硕士, 主要研究方向为导航、制导与控制
    李运迁(1982—), 男, 高级工程师, 博士, 主要研究方向为导航、制导与控制

Cooperative trajectory planning method in later part of midcourse based on velocity estimation

Zhengda CUI1,*, Mingying WEI1,2, Yunqian LI1   

  1. 1. Beijing Institute of Electric System Engineering, Beijing 100854, China
    2. Beijing Simulation Center, Beijing 100854, China
  • Received:2022-07-07 Online:2023-08-30 Published:2023-09-05
  • Contact: Zhengda CUI

摘要:

针对防空导弹中制导末段协同探测时间、空间、速度和角度的一致性弹道规划问题, 提出一种基于速度预测的协同弹道规划方法。考虑攻角、弹道、气动间的相互耦合和拦截弹被动减速特性, 借助半解析预测方法精准预报速度变化, 将需用过载转化为升力系数约束, 减少需处理的约束数量; 在此基础上, 通过弹道整形变量将多弹协同规划问题转化为非线性优化问题, 解析生成参考轨迹, 预报需用/可用过载; 综合改进粒子群优化算法, 采用自适应惯性权重和无效粒子再利用策略, 提高粒子利用率的同时提升种群脱离局部最优解的概率, 克服飞行散布和弹道偏差, 快速规划满足终端时、空、角一致性约束的中制导协同弹道。数学仿真验证了中制导末段多约束协同弹道规划算法的有效性。

关键词: 协同探测, 协同弹道规划, 改进粒子群优化

Abstract:

A synergistic guidance method is proposed for interceptor missiles in the later part of midcourse. For cooperative detection, time-to-go, range-to-go, terminal velocity and terminal angle should be controlled independently. The semi-analytic prediction method is used to predict the velocity, needed overload and supplied overload; convert the required overload into the lift coefficient requirements. The cooperative trajectory planning problem is transformed into a nonlinear optimization problem through the selection of trajectory shaping variables, and the reference trajectory is generated online. To improve the particle swarm optimization algorithm, adaptive inertia weight selection and invalid particle substitution strategy were adopted, which can improve the probability of the population and escaping from the local optimal point. Trajectory that meets the terminal constrains can be planning fast on consider of the flight dispersion and trajectory deviation. Finally the effectiveness is verified based on mathematical simulation.

Key words: cooperative detection, cooperative trajectory planning, improved particle swarm optimization

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