干扰及机动条件下的比例导引智能调控策略
|
摘要
由于红外诱饵干扰样式复杂、目标机动形式多变导致传统比例导引律极易被干扰。为提高采用比例导引方法的导弹性能,提出一种利用径向基函数网络调控比例系数及导弹发射时机的智能导引律。以飞行时间及脱靶量为参考,通过构建加权型指标函数将求解最优比例系数及发射时机问题转化为单目标优化问题;引入量子粒子群算法求解最优决策参量,并以其作为网络输出,干扰样式作为网络输入,离线训练径向基函数网络;为提高训练效率,结合K-means及K最近邻算法初始化径向基函数网络。仿真结果表明,当存在红外诱饵干扰时,智能导引律性能优于扩展比例导引律及自适应滑模导引律。
Due to the complicated interference pattern of the infrared decoy and the variable shape of the target maneuver,the traditional proportional guidance law is easily interfered. In order to improve the performance of missiles using the proportional guidance method,an intelligent guidance law that uses the RBF( radial basis function) network to control the proportional coefficient and the timing of missile launch is proposed.Taking the flight time and miss distance as reference,the weighted index function is used to transform the optimal proportional coefficient and launch timing problem into a single objective optimization problem. The quantum particle swarm optimization algorithm is introduced to solve the optimal decision parameters which are used as the network output,and the interference pattern is used as the network input to train the RBF network offline. To improve the training efficiency,the RBF network is initialized by combining the K-means and KNN( K nearest neighbors)algorithms. Simulation results show that the intelligent guidance law is better than the extended proportional guidance law and the adaptive sliding mode guidance law when there is infrared decoy interference.
Due to the complicated interference pattern of the infrared decoy and the variable shape of the target maneuver,the traditional proportional guidance law is easily interfered. In order to improve the performance of missiles using the proportional guidance method,an intelligent guidance law that uses the RBF( radial basis function) network to control the proportional coefficient and the timing of missile launch is proposed.Taking the flight time and miss distance as reference,the weighted index function is used to transform the optimal proportional coefficient and launch timing problem into a single objective optimization problem. The quantum particle swarm optimization algorithm is introduced to solve the optimal decision parameters which are used as the network output,and the interference pattern is used as the network input to train the RBF network offline. To improve the training efficiency,the RBF network is initialized by combining the K-means and KNN( K nearest neighbors)algorithms. Simulation results show that the intelligent guidance law is better than the extended proportional guidance law and the adaptive sliding mode guidance law when there is infrared decoy interference.
引文
[1]吕洁,罗勇,卿松,等.红外制导技术在空空导弹中的应用分析[J].兵器装备工程学报,2017,38(12):70-74.LYU Jie,LUO Yong,QING Song,et al. Application analysis of infrared guidance technology in air-to-air missile[J].Journal of Ordnance Equipment Engineering,2017,38(12):70-74.(in Chinese)
[2]Lin C M,Peng Y F. Missile guidance law design using adaptive cerebellar model articulation controller[J]. IEEE Transaction on Neural Networks,2005,16(5):636-644.
[3]Gu W J, Zhao H C, Zhang R C. A three-dimensional proportional guidance law based on RBF neural network[C]//Proceedings of 7th World Congress on Intelligent Control and Automation,2008:6978-6982.
[4]Lee Y L,Chen K Y,Liao S J. Using proportional navigation and a particle swarm optimization algorithm to design a dual mode guidance[J]. Computers and Electrical Engineering,2016,54(C):137-146.
[5]Hossain M A,Madkour A A M,Dahal K. P,et al. A realtime dynamic optimal guidance scheme using a general regression neural network[J]. Engineering Applications of Artificial Intelligence,2013,26(4):1230-1236.
[6]Aghunathan T,Ghose D. Differential evolution based 3-D guidance law for a realistic interceptor model[J]. Applied Soft Computing,2014,16(4):20-33.
[7]张志波,童中翔,王超哲,等.视线方向飞机红外辐射特性建模与仿真[J].激光与红外,2013,43(8):890-895.ZHANG Zhibo,TONG Zhongxiang,WANG Chaozhe,et al.Modeling and simulation of airplane infrared characteristic along the sightline[J]. Laser&Infrared,2013,43(8):890-895.(in Chinese)
[8]Yang C L,Sha Q D. Research on infrared decoy radiation characteristics and simulation[C]//Proceedings of IEEE10th Conference on Industrial Electronics and Applications,2015:1223-1227.
[9]Hu Y F,Song B F. Evaluation the effectiveness of the infrared flare with a tactic of dispensing in burst[C]//Proceedings of 3rd International Symposium on Systems and Control in Aeronautics and Astronautics,2010:131-136.
[10]Polasek M,Nemecek J,Pham I Q. Counter countermeasure method for missile's imaging infrared seeker[C]//Proceedings of 35th Digital Avionics Systems Conference,2016:1-8.
[11]Sun J, Xu W B,Feng B. A global search strategy of quantum-behaved particle swarm optimization[C]//Proceedings of Cybernetics and Intelligent Systems,2004:111-116.
[12]Zarchan P. Tactical and strategic missile guidance,progress in astronautics and aeronautics[M]. USA:AIAA Publications,2012.
[13]韩崇昭,朱洪艳,段战胜,等.多源信息融合[M]. 2版.北京:清华大学出版社,2010.HAN Chongzhao,ZHU Hongyan,DUAN Zhansheng,et al.Multi-source information fusion[M]. 2nd ed. Beijing:Tsinghua University Press,2010.(in Chinese)
[14]Zhou D,Mu C D,Xu W L. Adaptive sliding-mode guidance of a homing missile[J]. Journal of Guidance,Control,and Dynamics,1999,22(4):589-594.
[2]Lin C M,Peng Y F. Missile guidance law design using adaptive cerebellar model articulation controller[J]. IEEE Transaction on Neural Networks,2005,16(5):636-644.
[3]Gu W J, Zhao H C, Zhang R C. A three-dimensional proportional guidance law based on RBF neural network[C]//Proceedings of 7th World Congress on Intelligent Control and Automation,2008:6978-6982.
[4]Lee Y L,Chen K Y,Liao S J. Using proportional navigation and a particle swarm optimization algorithm to design a dual mode guidance[J]. Computers and Electrical Engineering,2016,54(C):137-146.
[5]Hossain M A,Madkour A A M,Dahal K. P,et al. A realtime dynamic optimal guidance scheme using a general regression neural network[J]. Engineering Applications of Artificial Intelligence,2013,26(4):1230-1236.
[6]Aghunathan T,Ghose D. Differential evolution based 3-D guidance law for a realistic interceptor model[J]. Applied Soft Computing,2014,16(4):20-33.
[7]张志波,童中翔,王超哲,等.视线方向飞机红外辐射特性建模与仿真[J].激光与红外,2013,43(8):890-895.ZHANG Zhibo,TONG Zhongxiang,WANG Chaozhe,et al.Modeling and simulation of airplane infrared characteristic along the sightline[J]. Laser&Infrared,2013,43(8):890-895.(in Chinese)
[8]Yang C L,Sha Q D. Research on infrared decoy radiation characteristics and simulation[C]//Proceedings of IEEE10th Conference on Industrial Electronics and Applications,2015:1223-1227.
[9]Hu Y F,Song B F. Evaluation the effectiveness of the infrared flare with a tactic of dispensing in burst[C]//Proceedings of 3rd International Symposium on Systems and Control in Aeronautics and Astronautics,2010:131-136.
[10]Polasek M,Nemecek J,Pham I Q. Counter countermeasure method for missile's imaging infrared seeker[C]//Proceedings of 35th Digital Avionics Systems Conference,2016:1-8.
[11]Sun J, Xu W B,Feng B. A global search strategy of quantum-behaved particle swarm optimization[C]//Proceedings of Cybernetics and Intelligent Systems,2004:111-116.
[12]Zarchan P. Tactical and strategic missile guidance,progress in astronautics and aeronautics[M]. USA:AIAA Publications,2012.
[13]韩崇昭,朱洪艳,段战胜,等.多源信息融合[M]. 2版.北京:清华大学出版社,2010.HAN Chongzhao,ZHU Hongyan,DUAN Zhansheng,et al.Multi-source information fusion[M]. 2nd ed. Beijing:Tsinghua University Press,2010.(in Chinese)
[14]Zhou D,Mu C D,Xu W L. Adaptive sliding-mode guidance of a homing missile[J]. Journal of Guidance,Control,and Dynamics,1999,22(4):589-594.