一种多系统导航卫星联合定轨网平差观测值定权方法
By grouping observations at a station-by-station and system-by-system level and estimating simplified Helmert variance components, combined with iterative weighted solutions based on robust estimation, the computational efficiency and accuracy issues of observation weighting in the adjustment of a multi-system navigation satellite joint orbit determination network were resolved. This achieved efficient adaptive observation weighting, improving the accuracy and reliability of joint orbit determination for multi-system navigation satellites.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2026-05-08
- Publication Date
- 2026-07-17
AI Technical Summary
In the adjustment of existing multi-system navigation satellite joint orbit determination networks, it is impossible to achieve adaptive observation weighting on a station-by-station and system-by-system basis while ensuring computational efficiency, which limits the improvement of accuracy.
An iterative weighted least squares solution framework combining station-by-station and system-by-system multi-granularity observation grouping, simplified Helmert variance component estimation (omitting redundant trace correction terms), and robust estimation is adopted. Data-driven adaptive observation weight estimation improves accuracy and reliability.
Without significantly increasing the computational burden, this study precisely characterizes the non-homogeneous characteristics of observations from different stations and navigation systems, thereby improving the orbital accuracy and solution reliability of joint orbit determination for multi-system navigation satellites.
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Figure CN122131355B_ABST