Outlier Detection in GNSS Coordinate Time Series Based on the DIA Approach
Abstract We solve the problem that the analysis of crustal deformation is affected by outliers in GNSS coordinate time series. Firstly, we introduce the classical data detection method DIA(detection, identification, adaptation) into the GNSS coordinate time series analysis. Then, we use an efficient DIA algorithm for outlier detection. Finally, we use the simulated data and the real data of the Crustal Movement Observation Network of China(CMONOC) to compare the DIA algorithm with the traditional 3σ method. The results show that the DIA algorithm can effectively detect the anomalous values in the GNSS coordinate time series with higher accuracy than the traditional 3σ method. Compared with the traditional DIA algorithm, the computational efficiency of the improved DIA algorithm is significantly improved.
Key words ：
GNSS coordinate time series
outlier detection
hypothesis testing
matrix inversion
Cite this article:
TAO Guoqiang,QIU Xiaomeng,LIU Dandan. Outlier Detection in GNSS Coordinate Time Series Based on the DIA Approach[J]. jgg, 2023, 43(6): 556-560.
TAO Guoqiang,QIU Xiaomeng,LIU Dandan. Outlier Detection in GNSS Coordinate Time Series Based on the DIA Approach[J]. jgg, 2023, 43(6): 556-560.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2023/V43/I6/556
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