摘要
在主被动雷达导引头目标跟踪过程中,为了有效融合主被动雷达导引头探测的信息进行精确跟踪,文中提出了用BP神经网络将主被动雷达导引头探测的信息进行分类,并通过模糊系统根据目标的机动大小调节神经网络的学习速率以及根据目标距离的远近调节融合中心的权值。通过仿真试验表明,与传统的目标跟踪方法相比较,具有更好的跟踪效果,证明了该方法是可行的。
During active and passive radar seeker tracking target, in order to effectively fuse information detected by two seekers for precise tracking, in this paper, BP neural network was used to classify the information into two different kinds, then fuzzy system was applied to adjust BP neural network＇ learning speed based on target＇ s maneuver extent, at the same time, adjust the fusion center＇ s parameter based on target＇ s distance. Computer simulation shows that compared with traditional method, this method can conduct target tracking perfectly, it is proved to be ascendant.
出处
《弹箭与制导学报》
CSCD
北大核心
2015年第3期5-8,共4页
Journal of Projectiles,Rockets,Missiles and Guidance
关键词
主被动雷达导引头
目标跟踪
神经网络
模糊系统
active and passive radar seeker
target tracking
neural network
fuzzy system
作者简介
张兴（1990-），男，安徽合肥人，硕士研究生，研究方向：神经网络与信息融合。
