针对车载跟瞄设备对低轨卫星进行跟踪时,采用传统的卫星轨道双行根数预报数据精度较低,而且在跟踪过程中遇到云雾遮蔽或天顶跟踪盲区时易发生目标丢失现象,提出利用单站车载跟瞄设备获得的实测数据,基于改进的拉普拉斯轨道预测方法对卫星轨道进行预测.考虑预测模型、测量轴系和坐标变换等多种原因造成的预测误差,讨论了减少误差的方法,并采用插值方法对预测偏差进行了误差修正,获得了较高精度的引导值.实验数据表明,对轨道数据进行7 s外推后,方位和俯仰预测精度可由双行根数预报的3′左右提高到10″量级,解决了卫星穿云或过天顶盲区时的稳定捕获跟踪问题.%When a vehicle-borne tracking and position device is used to track a Low Earth Orbit(LEO) satellite,the obtained prediction data of the satellite orbit by the traditional satellite tracking software usually show a lower prediction accuracy. Meanwhile, the target is missed easily because of the cloud or zenith blind zones during the target tracking. To improve the satellite orbit prediction, this paper presents a new method which uses the improved Laplace method to predict satellite orbits based on the measured data by the vehicle-borne tracking and position device. In consideration of the prediction errors come from the prediction model, measuring axis and the coordinate transfer, it proposes an interpolation method to correct the error between predicted value and actual measured value and to obtain a higher accuracy direction value. The testing data show the accuracy of predicted data has increased from 3′to 10″ in azimuth and elevation when the data are extrapolated to 7 s, which realizes the stable satellite tracking in the cloud or zenith blind zones.
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