Impact of Time Span and Missing Data on the Noise Model Estimation of GNSS Time Series

• DOI: 10.20944/preprints202306.1667.v1
• Publication Date: 2023-06-25T05:11:56Z
• Authors: Xiwen. Sun; Tieding Lu; Shunqiang Hu; Jiahui. Huang; Xiaoxing. He; Jean-Philippe Mon...; Xiaping Ma; Zhengkai Huang

Noise model selection criteria has a significant impact on identifying the stochastic noise proper-ties of any GNSS daily coordinate time series. The low-frequency random walk existing in these series could lead to overestimation tectonic rate, so it is great significance accurately detect component. This study focuses estimation cri-terion (BIC_tp) derived from AIC and BIC by introducing 2π factors. It more sensitive abnormal steps (random jumps). Using observation data 72 stations 1992 2022 simulated data, four combined models are used explore impacts se-ries lengths (ranging from2 24 years) loss (between 2% 30%) velocity estimation. results show that as length increased, selected optimal model, estimated uncertainty trend with different gap, gradually con-verge. When short (less than 8 years), FNRWWN, FNWN, PLWN being mistakenly GGMWN models, thereby affecting accura-cy determining station parameters. 12 years, RW component probably detected, As increases, weakened. Finally, we conclude for minimum both ve-locity parameters reliable.