实时估计不同类型北斗卫星观测值的随机模型

为分析北斗卫星观测值随机特性，估计了地球静止轨道、倾斜地球同步卫星轨道、中地球轨道卫星载波相位观测值的方差分量。发现不同接收机和不同类型卫星观测值方差分量的大小和时变特性具有明显差异。为构建更切实际的方差结构随机模型，提出利用迭代最小二乘和最小范数二次无偏估计相结合的方法，实时估计不同类型北斗卫星观测值方差分量。为评估实时估计随机模型的性能，对243 m、645 m、10 137 m三条不同长度基线进行精密相对定位测试，结果表明:实时估计随机模型能有效改善北斗卫星精密单历元动态相对定位性能，尤其当站间距离较长时改善更显著。10 137m基线测试结果表明，1h数据单历元解在北、东、高方向，平均定位精度分别提高了41.3%、54.5%、51.6%，稳定性分别提高了38.4%、17.7%、39.7%。

Real-Time Estimating Different Types of BDS Observations Stochastic Model

In order to analze the stochastic characteristics of BDS (BeiDou satellites) observations, GEO(geostationary earth orbit),IGSO(inclined geosynchronous satellite orbit),MEO(medium earth orbit) satellites observations variance components are estimated. The observation variance components of different receivers and different types of BDS are proved to be significantly different in size and time-varying characteristics. To deal with the heterogeneous variances, a real-time estimating BDS observations stochastic model procedure is developed with the methods of iterative least-squares and MINQUE(minimum norm quadratic unbiased estimation).To demonstrate its performance, precise relative positioning experiments are carried out using 243m, 645m and 10 137 m baselines, respectively. In contrast to the empirical stochastic model, the real-time estimating stochastic model can improve the performance of BDS precise relative positioning, and improve more significantly for the longest baseline.10 137 m baseline test results indicate that the real-time estimating stochastic model can improve mean positioning precision 41.3%、54.5%、51.6% and RMS values of multi-epoch position offsets 38.4%、17.7%、39.7% in N(north), E(east), U(up) direction respectively.