空间监视雷达高精度实时目标定轨方法

A Real⁃Time Orbit Determination Method for Space Surveillance Radar

地基空间监视雷达肩负着新目标发现、编目维持、空间事件监视等太空态势实时感知任务。在太空态势实时感知任务中,必须对空间目标进行实时高精度目标定轨。这类任务对实时性和精度要求都很高,传统方法难以满足任务需求。例如,传统的空间目标定轨算法为事后处理,为达到任务的精度要求需要积累多天多圈数据,不能满足此类任务的实时性要求。而传统的雷达目标跟踪滤波算法仅支持单弧段,其精度无法达到应用要求。为此,本文提出了基于高精度空间目标轨道模型和空间目标轨道预报误差协方差传播理论的不敏卡尔曼滤波(UKF)。该方法采用高精度空间目标轨道模型,支持多装备多弧段雷达观测数据,可以很好地解决多弧段滤波中断导致协方差不匹配的问题。根据仿真实验,跟踪三圈后,实时定轨的目标位置精度可以达到百米级,速度精度达到分米级。

Ground⁃based surveillance radar undertakes various real⁃time space situational awareness tasks,such as finding new targets,space object catalogue maintenance,and space event surveillance.During real⁃time space situa⁃tional awareness tasks,it is essential to do real⁃time orbit determination.Such tasks require strong timeliness and high precision,while conventional methods can hardly meet the requirements.For example,the frequently⁃used orbit determi⁃nation method is post processing,which has to accumulate several cycles during many days to obtain high precision and cannot determine orbit in real time.Also,the filter methods used in radar only support single arc,and the obtained preci⁃sion is not high enough for real⁃time space situational awareness tasks.Therefore,this article proposes a new UKF meth⁃od based on high precision orbit model and covariance propagation theory.This method supports multi⁃equipment and multi⁃arc observations,and can match the covariance with different arcs.According to simulation,using this method,after 3 cycles,the target position error can converge to the order of 100 m,and the velocity error can converge to the order of 10 cm/s.