针对太阳光压是精密定轨的重要误差来源,该文对超快速轨道预报部分的几种光压模型进行分析,对比不同影响,其中包括5参数ECOM1、9参数ECOM2、7参数ECOM3模型及先验模型Box-wing.结果表明,Box-wing先验模型可以有效提高超快速轨道精度.对于GPS(ⅡF/ⅡR)、Galileo(IOV/FOC)和GLONASS(M/K)卫星,ECOM2+BW模型具有更好表现,非地影时刻超快速轨道6 h预报轨道精度分别为4.97、7.66和7.73 cm.BDS(CAST/SECM)卫星采用ECOM1+BW模型精度为8 cm.添加Box-wing先验模型对卫星进入地影期后的快速轨道精度也有所提升.对不同采样间隔情况下的超快速轨道数据处理耗时以及轨道重叠精度进行分析发现,随着采样间隔时间的增加,数据处理耗时缩短,重叠弧段轨道精度逐渐降低.在兼顾精度与耗时的情况下,超快速轨道产品生成过程中设置处理间隔为600 s.
GNSS ultra-rapid orbit prediction with the aid of the constraint of solar radiation pressure models and sampling intervals
In view of the fact that solar pressure is an important source of error in precision orbit determination,this article analyzes several pressure models for ultra fast orbit prediction and compares their different effects,including the 5 parameters ECOM1,9 parameters ECOM2,7 parameters ECOM3 model,and a prior model Box-wing.The results indicate that the Box-wing prior model can effectively improve the accuracy of ultra fast orbits.For GPS(ⅡF/ⅡR),Galileo(IOV/FOC),and GLONASS(M/K)satellites,the ECOM2+BW model performs better,with predicted orbit accuracies of 4.97 cm,7.66 cm,and 7.73 cm for ultra fast orbit 6 hours during non Earth shadow periods,respectively.The BDS(CAST/SECM)satellite adopts an ECOM1+BW model with an accuracy of 8 cm.The addition of a Box wing prior model has also improved the fast orbit accuracy of satellites entering the shadow period.Analysis of the processing time and orbit overlap accuracy of ultra fast orbit data under different sampling intervals reveals that as the sampling interval time increases,the data processing time shortens and the accuracy of overlapping arc segment orbits gradually decreases.Setting a processing interval of 600 s during the ultra fast track product generation process while balancing accuracy and time consumption.
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