滑翔导弹末段多约束智能弹道规划

邵会兵; 韦常柱

doi:10.3788/OPE.20192702.410

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滑翔导弹末段多约束智能弹道规划

微纳技术与精密机械 | 更新时间：2020-08-13

- 滑翔导弹末段多约束智能弹道规划
- Multi-constrained intelligent trajectory planning for gliding missiles
- 光学精密工程 2019年27卷第2期页码：410-420
- 作者机构：
  
  哈尔滨工业大学航天学院，黑龙江哈尔滨 150006
- 作者简介：
  
  [ "邵会兵(1977-)，男，江西南城人，研究员，博士生，1998年于哈尔滨工程大学获得学士学位，2005于航天科工二院研究生院导航制导与控制专业获得硕士学位，主要从事智能弹道规划与制导方面的研究。E-mail：shaohuibingshb@163.com" ]
  韦常柱(1982-)，男，黑龙江佳木斯人，博士，副教授，2004年、2010年于哈尔滨工业大学分别获得学士、博士学位，主要从事飞行器制导与控制研究。E-mail：weichangzhu@hit.edu.cn WEI Chang-zhu, E-mail: weichangzhu@hit.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(61403100);中央高校基本科研业务费专项资金资助(HIT.NSRIF.2015.037);微小航天器技术国防重点实验室开放基金资助项目(HIT.KLOF.MST.201704);哈尔滨市科技创新人才专项基金资助项目(2015RQQXJ089)
- DOI：10.3788/OPE.20192702.410
  中图分类号： V448.2
- 收稿日期：2018-08-09，
  
  录用日期：2018-9-13，
  
  纸质出版日期：2019-02-15
- 稿件说明：
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邵会兵, 韦常柱. 滑翔导弹末段多约束智能弹道规划[J]. 光学精密工程, 2019,27(2):410-420.

Hui-bing SHAO, Chang-zhu WEI. Multi-constrained intelligent trajectory planning for gliding missiles[J]. Optics and precision engineering, 2019, 27(2): 410-420.
邵会兵, 韦常柱. 滑翔导弹末段多约束智能弹道规划[J]. 光学精密工程, 2019,27(2):410-420. DOI： 10.3788/OPE.20192702.410.

Hui-bing SHAO, Chang-zhu WEI. Multi-constrained intelligent trajectory planning for gliding missiles[J]. Optics and precision engineering, 2019, 27(2): 410-420. DOI： 10.3788/OPE.20192702.410.

摘要

滑翔导弹末段飞行时空复杂度高、不确定性强、约束多，给弹道规划与制导算法带来了较大的建模和求解难度。针对这一问题，同时增大末段机动范围并提高弹道规划效率，本文提出一种利用连续型深度置信神经网络(Convolutional Deep Brief Networks，CDBN)预测机动能力、设计经由点状态实现末段多约束智能弹道规划的方法。过程中采用CDBN对机动能力进行在线预测，快速判定经由点状态的可行性，并且通过经由点状态智能设计，实现前后段能量的优化分配，扩大弹道机动包络；通过设计三角函数型弹目视线角实现末段弹道摆动机动，推导机动弹道最优末制导律对视线角进行跟踪，并调节机动频率以满足速度约束。仿真结果表明，CDBN相对BP网络具有更高的机动能力预测精度；本文所提智能弹道规划方法在满足末端速度约束的前提下，可以实现弹道摆动机动并大幅增加飞行包络。弹道规划能够在0.5 s内完成，满足工程应用的快速性要求。

Abstract

The terminal flight of the gliding missile involves high complexity

strong uncertainty

and many constraints. It is difficult to model and solve the corresponding trajectory planning and guidance problems. To increase the maneuvering range of the gliding missile and reduce the difficulty of trajectory planning

a multi-constrained trajectory intelligent planning method was proposed. This method included waypoint design and maneuverability prediction using the Continuous Deep Belief Network (CDBN). The CDBN was used to predict the maneuvering ability online

and the feasibility of the waypoint´s state was determined rapidly. With the intelligent design of the waypoints

optimized allocation of energy was realized

which increases the flight envelope. To realize oscillatory maneuvering

the Line of Sight (LOS) relative to the target was designed as a trigonometric function

which was tracked by designing the optimal maneuvering guidance law. Finally

the desired velocity constraint was satisfied by adjusting the frequency of the LOS angle. The simulation results show that the CDBN has higher maneuverability prediction accuracy than the BP network. The proposed method can realize oscillatory maneuvering and achieve a large increase in the flight envelope while satisfying the terminal velocity constraint. Online trajectory planning based on the CDBN can be completed in half a second

which satisfies the rapidity requirements for engineering applications.

关键词

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