模糊聚类定权法对SLR定轨精度的影响

Effect analysis of the weighting scheme with modified FCM clustering algorithm on precision of SLR orbit determination

针对卫星激光测距(satellite laser ranging,SLR)精密定轨过程中存在的测站观测数据合理定权问题,将一种改进的模糊聚类算法引入到SLR观测数据定权中。基于国际激光测距服务(International Laser Ranging Service,ILRS)提供的全球SLR测站性能报告,对测站进行近实时滑动分类定权,改变SLR数据处理中权重的经验或者随意性选取模式。经过LAGEOS1卫星2014年1月至2016年12月3年全球SLR实测数据处理的测试。结果表明,当考虑LAGEOS标准点总数、LAGEOS标准点RMS值以及LAGEOS标准点合格率这3项测站质量控制因素确定的测站权值能最大限度地提高卫星定轨精度和观测数据的使用效率,对参与计算的365个3d弧段数据,91.46%弧段精度得到提高,平均提高约3.7mm,且每个测站的定轨残差RMS也得到了降低。这对于正在迈向毫米级测量精度的SLR技术至关重要。

As to the problem of reasonable weighting of station observations in the precise orbit determination of satellite laser ranging (SLR), a modified fuzzy c-means(FCM) clustering algorithm is introduced into the determination of the weights of SLR station observations. Based on the SLR global performance report card provided by the International Laser Ranging Service (ILRS), it is performed that a near real-time sliding reweighting of the station, aiming to change the experienced or somewhat arbitrary weights in the SLR data processing. The orbit of satellite LAGEOS 1 from Jan. 2014 to Dec. 2016 is computed from the SLR data. The results show that the clustering carried out considering only the three variables in the SLR global performance report card: LAGEOS normal point volume, LAGEOS normal point RMS, and percentage of LAGEOS normal point accepted can improve the precision of orbit determination and the efficiency of station observations to the maximum extent. For the 365 3-day arcs involved in the calculation, the precision of the 91.46% arc segment is improved, and the average increase is about 3.7 mm. Additionally, the root mean square (RMS) of the observational residual of individual station is also reduced, which is crucial for SLR technology that is moving towards millimeter-scale measurement precision.