【摘要】 针对延迟环节，提出一种使用基于改进的离散系统最速控制综合函数的跟踪微分器的直接预测补偿法，提取延迟信号的跟踪及微分信号，根据跟踪信号和原信号的间距来自适应调整跟踪微分器的参数，并根据泰勒展开补偿对延迟环节进行补偿。针对采样保持环节，引入根据当前加速度调整加速度极值的机动目标修正的“当前”统计模型，以及设计基于修正的“当前”统计模型的自适应调整预测协方差的卡尔曼滤波(Kalman filter,KF)，并针对采样保持环节的特性对观测噪声的协方差矩阵进行实时调整，实现对采样保持环节的补偿。实验仿真结果表明：所提脱靶量补偿方法有效降低了延迟环节和采样保持环节带来的影响，具有可与其他先进脱靶量补偿方法相等的性能。更多还原

【Abstract】 For the delay link, a direct predictive compensation method using a tracking differentiator based on an improved discrete system optimal control synthesis function is proposed to extract the tracking and differential signals of the delay signal, adaptively adjust the parameters of the tracking differentiator according to the distance between the tracking signal and the original signal, and compensate the delay link according to the Taylor expansion compensation. For the sample-and-hold process, a modified “current” statistical model is introduced to adjust the acceleration extremum of the maneuvering target according to the current acceleration, and a Kalman filter is designed to adaptively adjust the prediction covariance based on the modified “current” statistical model, and the covariance matrix of the observation noise is adjusted in real time according to the characteristics of the sample-and-hold process, so as to compensate the sample-and-hold process. The simulation results show that the proposed miss distance compensation method can effectively reduce the impact of delay and sample-and-hold, and has comparable performance with other advanced miss distance compensation methods.更多还原