利用自适应卡尔曼滤波实现光电跟踪中的复合控制

为了在光电跟踪控制系统中实现复合控制以提高跟踪精度,构建了基于模型自适应卡尔曼滤波算法的复合控制结构。首先,利用跟踪脱靶量数据和仪器位置数据合成目标角位置数据;然后,利用模型自适应卡尔曼滤波算法对目标角位置数据进行滤波估计以获得目标角速度信息;最后,将目标角速度信息前馈到速度回路,从而构成复合控制系统。实验结果表明:采用复合控制结构后,目标跟踪精度提高了50%。基于模型自适应卡尔曼滤波算法的复合控制技术能够在保持原反馈控制系统稳定性的条件下提高跟踪精度。

Compound control of photoelectric tracking by using adaptive Kalman filtering algorithm

In order to realize compound control for improving tracking accuracy in photoelectric tracking control system,a compound control structure based on adaptive Kalman filtering algorithm for model was established.Firstly,the angular position data of the target was compounded by taking advantages of tracking miss distance data and instrument position data;Then,the angular position data of the target was subject to filtering estimation in order to obtain angular velocity of the target by taking advantages of adaptive Kalman filtering algorithm for model;Finally,the compound control system was established by front feeding the angular velocity of the target to the velocity loop.The experimental result shows that target tracking accuracy is increased by 50％ after using the compound control system.Based on adaptive Kalman filtering algorithm for model,under the condition of keeping the stability of the original feedback control system,the tracking accuracy of the compound control system can be improved.