Jason-2卫星搭载了第三代DORIS接收机DGXX,与前两代接收机相比,DGXX在时效性和数据量上都有显著提高。本文研究了DGXX接收机输出的相位观测数据与传统的Doppler数据之间的转换,并通过内符精度比较、轨道重叠检验、独立轨道比较及卫星激光测距(SLR)检验分析了DORIS数据独立定轨和SLR+DORIS数据联合定轨精度及SLR在联合定轨中的贡献。另外,考虑到部分DORIS地面信标站气象数据可能不够精确或缺失会影响DORIS数据中对流层延迟模型改正精度,本文通过和实测气象数据比较分析了最新的气象参数模型GPT在DORIS定轨中的应用及其对定轨精度的影响。计算结果表明:GPT模型和DORIS地面信标站实测气象数据的定轨精度相当,在无实测气象数据情况下可利用GPT模型替代;DORIS数据独立定轨和SLR+DORIS联合定轨径向均能达到1cm精度,SLR+DORIS联合定轨精度略优于DORIS独立定轨精度,联合定轨中SLR的主要贡献是能降低解算参数中的湿天顶延迟和DORIS频率漂移的相关性、保持轨道精度的长期稳定性。
The DORIS instrument called DGXX on Jason-2 satellite is the first of the third generation. Compared to the previous two generations, both data efficiency and tracking capability of DGXX have been improved significantly. Firstly, transformation between phase data of DGXX and traditional Doppler data is described in this paper, and then the accuracies of orbits determined by using DORIS data only and DORIS data combined with SLR data are assessed through various methods including post-fit RMS comparison, orbit overlapping validation, independent orbit comparison and SLR validation. In addition, considering if real meteorological data of some stations are not available or inaccurate, that the accuracy of the troposhperic delay correction model can be affected the use of a new Global Pressure and Temperature (GPT) model in DORIS precise orbit determination (POD) is therefore discussed in this paper. It is demonstrated that the orbit accuracy with GPT model and real meteorological data is at the same level, therefore GPT-derived data is an eligible substitute once some real meteorological data are missing. Apart from that, Both orbit solutions witll DORIS only data and DORIS combined with SLR data can reach 1 cm accuracy level at radial direction, the one with both DORIS and SLR data is slightly better than that with DORIS data only. The main contribution of SLR data to DORIS + SLR POD is to reduce the correlation between those two types of parameters of zenith tropospheric delay and DORIS frequency drift; long-stable POD can benefit from this particular advantage.