不同观测环境中的多模GNSS数据质量自动化检测方法

Automated detection methods for multimode GNSS data quality in different observation environments

受到GNSS轨道位置变化及其多模环境变化等多因素的共同影响,传统GNSS数据质量检测方法出现数据钟差偏差较大,局部GNSS数据实际检测结果与观测结果之间差距较大,无法为使用者提供准确的科学依据。为了解决偏差问题,提出3种优化方法。首先对多模GNSS数据实时轨道及钟差进行计算;然后对不同观测环境中的多模GNSS数据质量进行针对性分析;最后完成数据质量自动化评价输出。通过设计的实验表明,经过提出方法优化后的各项检测指标优化效果明显,检测准确度大幅度提升,稳定性明显改善,整体性能可满足当前不同观测环境下多模GNSS数据之间自动化检测任务,文中方法具有较高的研究价值与市场推广价值。

Due to the combined influence of multiple factors such as changes in GNSS orbit position and multimodal environment,traditional GNSS data quality detection methods have significant clock bias,and there is a significant gap between the actual detection results and observation results of local GNSS data,which cannot provide accurate scientific basis for users.In order to solve the deviation problem,three optimization methods are propsed in this paper.First,calculate the real-time orbit and clock deviation of multi-mode GNSS data;then conduct targeted analysis on the quality of multimodal GNSS data in different observation environments;finally,complete the automated evaluation output of data quality.The designed experiments show that the optimization effect of various detection indicators after the proposed method optimization is significant,stability is greatly improved,the detection stability of the method is significantly improved,and the overall performance can meet the automated detection tasks between multimodal GNSS data in different observation environments.The method in this paper has high research value and market promotion value.