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应用科学学报 ›› 2012, Vol. 30 ›› Issue (3): 317-323.doi: 10.3969/j.issn.0255-8297.2012.03.017

• 论文 • 上一篇    下一篇

基于混合粒子群优化的巡航导弹低空突防航迹规划

王建青， 李帆， 赵建辉   

  1. 北京航空航天大学仪器科学与光电工程学院，北京100191
  • 收稿日期:2011-04-17 修回日期:2011-09-22 出版日期:2012-05-30 发布日期:2012-05-30
  • 通信作者: 李帆，副教授，研究方向：航天器制导与控制、智能算法，E-mail：lifan@buaa.edu.cn E-mail:lifan@buaa.edu.cn
  • 作者简介:李帆，副教授，研究方向：航天器制导与控制、智能算法，E-mail：lifan@buaa.edu.cn
  • 基金资助:

    国家自然科学基金（No.91016004）资助

Route Planning in Low Altitude Penetration for Cruise Missile Based on a Hybrid Particle Swarm Optimization

WANG Jian-qing, LI Fan, ZHAO Jian-hui   

  1. School of Instrument Science and Opto-electronics Engineering,Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2011-04-17 Revised:2011-09-22 Online:2012-05-30 Published:2012-05-30

PDF

1131

被引次数

7

摘要：

将模拟退火算法嵌入到粒子群优化（partical swarm optimization, PSO）算法中，并对PSO产生的最优适应值进行重新评价，以此构成混合粒子群优化算法（PSO-SA）. 将PSO-SA 算法应用于巡航导弹的航迹规划，不仅可以避免PSO陷入局部最优，而且能快速有效地完成离线和在线规划任务，获得理想的三维航迹. 仿真结果验证了该算法的有效性，且对同一起始位置所规划出的航程较PSO算法短，可有效节约导弹燃料.

关键词: 低空突防, 离线规划, 在线规划, 粒子群优化, 模拟退火

Abstract:

 A hybrid planning algorithm PSO-SA is presented, which is an integration of the simulated annealing algorithm (SA) and the particle swarm optimization (PSO) algorithm. PSO-SA is used to evaluate the optimal fitness value generated by PSO. PSO-SA used in route planning of cruise missile can avoid the common defect of premature convergence, accomplish the static and dynamic route planning assignment quickly, and
produce an ideal 3-D flight path. Simulations demonstrate feasibility of the algorithm. Compared to PSO, PSO-SA achieves a shorter range in the same initial locations, thus, cruise missiles consume less fuel.

Key words: low altitude penetration, static route planning, dynamic route planning, particle swarm optimization (PSO), simulated annealing (SA)

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