基于BP神经网络的闭路制导改进方法

针对传统闭路制导方法中的制导方法误差,提出了一种根据"真实目标"进行制导的改进制导方法。采用BP神经网络逼近算法,推导建立预定关机点及落点坐标与需要速度间的映射关系,并装订上弹,使关机点附近对应每一个位置能够映射出相应的需要速度矢量。然后利用闭路制导关机及导引方法对导弹实施控制。通过仿真,该方法大大减小了制导方法误差,提高了导弹射击精度。

An Improved Approach to Closed-Loop Guidance Based on BP Neural Network

To the guidance method error of traditional Closed-Loop guidance,according to“real target”,an improved guidance method is put forward. Mapping relation between the burnout and droppoint coordinates and required velocity is established by the use of BP neural network approximation algorithm,which would be bound to the missile so that required velocity can be computed around the burnout coordinate. Then the missile is controlled by the Close-Loop guidance law. It can reduce the guidance method error and improve the ballistic missile accuracy.