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基于联邦网络的传递对准滤波补偿算法

Keywords: 空空导弹,传递对准,联邦网络,补偿

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Abstract:

针对空中环境各种干扰因素对空空导弹传递对准(TA)滤波的影响,提出一种基于联邦网络的补偿算法.将干扰误差考虑为量测输入纳入滤波系统,改进标准Kalman滤波结构.将补偿神经网络设计成联邦结构,两个子系统分别用于训练量测输入估计误差、输出层权值误差和隐层权值误差.推导了联邦网络的训练算法并对算法进行了稳定性证明,保证了网络在结构上计算量小,系统反馈能力强,能够对干扰误差进行有效在线预测,辅助改进Kalman滤波器对失准角进行精确估计.仿真比较实验验证了该算法能够在不需任何先验信息的条件下,及时适应对准环境,预测校正干扰误差,滤波收敛快、精度高,适合空空导弹在具体设备和环境条件下的快速精确传递对准.

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