光电跟踪系统计算机辅助控制实现  

Implementation of Computer-Aided Control for Photoelectric Tracking System

作　　者：颜世刚[1] 刘少伟[1] 柳磊[1] 

机构地区：[1]92941部队94分队

出　　处：《光学与光电技术》2009年第3期45-48,共4页Optics & Optoelectronic Technology

摘　　要：建立了基于数值微分的目标运动状态滤波预测模型,用s-函数实现了卡尔曼滤波预测算法。利用目标位置拟合方法给出角位置信息,并以此为观测信息通过卡尔曼滤波预测出当前角位置和角速度信息,将其引入跟踪控制系统中以克服脱靶量滞后问题,同时也实现了系统的等效复合控制。仿真结果表明,基于数值微分的模型适用于角度跟踪,滤波预测具有较好的鲁棒性。通过对两个不同等效正弦输入的验证,可知角位置合成精度对共轴跟踪影响较大,在脱靶量和跟踪架角位置采样匹配对应时,跟踪仿真精度较高,而对等效复合控制跟踪误差影响较小,输入信号角频率增大时误差增大。The target motion state filtering model and combined filtering-predicting model are constructed based on numerical differentiation, using s-function to implement Kalman filter algorithm. The target angle position is worked out by manual position fitting, which is regarded as the observation of Kalman filter; Then the current angle position and velocity can be predicted to overcome the problem of off-target sample delay, and the equivalent combined control of the tracking system is carried out. The simulation results show that the model based on numerical differentiation is suitable for angle tracking, and filtering-predicting has preferable robustness. Verified by two different equivalent sine input signals, it is indicated that angle synthesis error has great effect on tracking precision of on-axis tracking. When the off-target measure and instrument position are matched, tracking simulation result is much better. The tracking error increases with the increasing of the input signal angle frequency.

关 键 词：数值微分 光电跟踪 等效复合控制 共轴跟踪 卡尔曼滤波 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]