基于多源数据融合的GEO目标轨道改进分析

Differential Correction Analysis of GEO Objects Based on Multi-source Data Fusion

以美国新一代天基监视卫星SBSS为例,构建了天地联合方式观测GEO目标的观测模型。同时作为对比,介绍了传统地基雷达的距离测量模型;提出了将天地联合测量数据与传统地基测距数据融合,利用扩展卡尔曼滤波(extended Kalman filter,EKF)对GEO目标进行轨道改进的方法。仿真结果表明,利用2种不同方式的观测数据对GEO目标轨道进行改进,得到的定轨误差效果好于只有一种测量数据的结果。

In the case of Space Based Surveillance Satellite （SBSS）, we constructed a spaceground joint GEO objective observation model. As a contrast, we have also introduced the traditional range measurement model of ground-based radar and put forward an approach of data fusion, which consists of space-ground joint observation data and ground-based radar range measurement data, making differential correction for GEO object by EKF. The simulation experiments show that it can get a better differential correction result of GEO object with fused data than independent data.