基于数据质量分析的TECR周跳处理算法

A TECR Cycle-slip Processing Algorithm Based on Data Quality Analysis

  • 摘要: 针对电离层活跃期或磁暴发生时,现有周跳探测算法未能正确探测并修复周跳的问题,提出了基于数据质量分析的电离层总电子含量变化率(以下简称电离层速率,TECR)拟合残差算法。通过对电离层拟合残差进行数据质量分析,可自适应确定最优拟合历元数,利用此历元数拟合得到的TECR拟合值可有效削弱电离层延迟影响。为保证周跳修复的准确性,采用搜索再判定与TECR补充检测方法对周跳修复值进行验证与确认。通过高电离层延迟条件下的实测数据对本文算法进行验证分析,实验结果表明该方法能够消除电离层延迟影响,实现电离层活跃期时的周跳探测与修复。

     

    Abstract: The existing cycle-slip detection algorithm usually can not detect and repair cycle-slips correctly in the ionospheric activity phase or when magnetic storms happen, this paper proposes a new algorithm for the fitted residual of the ionospheric total electronic content(TEC) rate (TECR) based on data quality analysis. By analyzing the data quality of the fitted TECR residual, we determine the optimal fitted epoch count adaptively and with this fitted epochs count can obtain a fitted TECR to weaken the influence of ionospheric error effectively. In order to ensure that the repaired cycle-slip is correct, the repaired value is validated by search re-determination and TECR complementary detection. Measured data is used to validated this algorithm. The experimental results show that this algorithm can realize the zero-difference dynamic real-time cycle-slip detection and repair the ionospheric activity phase.

     

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