Gross Error Data Processing Method for GNSS Deformation Monitoring Time Series
Abstract The performance of the traditional gross error detection algorithm for GNSS deformation monitoring is limited by the data length, so we propose a first-order derivative gross error elimination method based on wavelet analysis. First, we use the new algorithm to remove gross errors from the original signal, and then use generalized continuation interpolation to supplement the residual defects. The actual measurement results show that the execution time of the new algorithm is 0.01 times that of the 3-times medium-error method (3σ method), and the deviation from the real value after interpolation is only 0.03 mm, which is much better than other traditional gross error detection methods.
Key words :
GNSS deformation monitoring
gross error elimination
generalized continuation interpolation
wavelet transform
first-order derivative
Cite this article:
WANG Mindun,SHANG Junna. Gross Error Data Processing Method for GNSS Deformation Monitoring Time Series[J]. jgg, 2022, 42(12): 1246-1249.
WANG Mindun,SHANG Junna. Gross Error Data Processing Method for GNSS Deformation Monitoring Time Series[J]. jgg, 2022, 42(12): 1246-1249.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2022/V42/I12/1246
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