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应用科学学报 >

2012 , Vol. 30 >Issue 3: 317 - 323

DOI: https://doi.org/10.3969/j.issn.0255-8297.2012.03.017

论文

基于混合粒子群优化的巡航导弹低空突防航迹规划

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  • 北京航空航天大学仪器科学与光电工程学院，北京100191
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

收稿日期: 2011-04-17

  修回日期: 2011-09-22

  网络出版日期: 2012-05-30

基金资助

国家自然科学基金（No.91016004）资助

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

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  • School of Instrument Science and Opto-electronics Engineering,Beijing University of Aeronautics and Astronautics, Beijing 100191, China

Received date: 2011-04-17

  Revised date: 2011-09-22

  Online published: 2012-05-30

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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

本文引用格式

王建青， 李帆， 赵建辉 . 基于混合粒子群优化的巡航导弹低空突防航迹规划[J]. 应用科学学报, 2012 , 30(3) : 317 -323 . DOI: 10.3969/j.issn.0255-8297.2012.03.017

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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