Regional spatio-temporal zenith tropospheric delay modelling using independent component analysis

Dai, Wujiao; Yan, Hongge; Chen, Biyan; Liu, Bin

doi:10.1080/00396265.2018.1515812

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…GNSS sites are mostly deployed with deep anchors in bedrock or anchored through reinforced concrete structures and stable buildings (Xi et al 2021;Xu et al 2022); thus, these monitoring sites have fixed location properties. Furthermore, their errors can be suppressed by performing multisite combination networking calculations and error modeling (Dai et al 2019;Guns et al 2022). However, InSAR technology is limited by its own imaging and positioning principles, resulting in a lack of an absolute reference frame for monitoring data, while the achieved monitoring precision is easily affected by factors such as orbital and atmospheric errors (Yang et al 2020;Lee and Shirzaei 2023).…”

Section: Introductionmentioning

confidence: 99%

A method for correcting InSAR interferogram errors using GNSS data and the K-means algorithm

Yan,

Dai,

et al. 2024

Earth Planets Space

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Correcting interferometric synthetic aperture radar (InSAR) interferograms using Global Navigation Satellite System (GNSS) data can effectively improve their accuracy. However, most of the existing correction methods utilize the difference between GNSS and InSAR data for surface fitting; these methods can effectively correct overall long-wavelength errors, but they are insufficient for multiple medium-wavelength errors in localized areas. Based on this, we propose a method for correcting InSAR interferograms using GNSS data and the K-means spatial clustering algorithm, which is capable of obtaining correction information with high accuracy, thus improving the overall and localized area error correction effects and contributing to obtaining high-precision InSAR deformation time series. In an application involving the Central Valley of Southern California (CVSC), the experimental results show that the proposed correction method can effectively compensate for the deficiency of surface fitting in capturing error details and suppress the effect of low-quality interferograms. At the nine GNSS validation sites that are not included in the modeling process, the errors in the ascending track 137A and descending track 144D are mostly less than 15 mm, and the average root mean square error values are 11.8 mm and 8.0 mm, respectively. Overall, the correction method not only realizes effective interferogram error correction, but also has the advantages of high accuracy, high efficiency, ease of promotion, and can effectively address large-scale and high-precision deformation monitoring scenarios. Graphical Abstract

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Section: Introductionmentioning

confidence: 99%

A method for correcting InSAR interferogram errors using GNSS data and the K-means algorithm

Yan,

Dai,

et al. 2024

Earth Planets Space

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“…The BSSs are regarded as convenient and practical ZTD modeling methods, particularly for modeling spatiotemporal features, where the direct processing of high-dimensional raw data can be avoided, the efficiency of data processing can be improved, and the spatiotemporal features of data can be better understood. Dai et al [31] established empirical ZTD models in China and the United Kingdom using ICA, and their models with centimeter accuracy outperformed the UNB3 and GPT2w models. However, their time resolution is only one day, but the present ZTD model requires a higher time resolution when used in GPS water vapor applications.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Forecasting the GPS Zenith Troposphere Delay in West Antarctica Based on Different Blind Source Separation Methods and Deep Learning

Zhang

et al. 2020

Sensors

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Tropospheric delay is an important error source in global positioning systems (GPS), and the water vapor retrieved from the tropospheric delay is widely used in meteorological research such as climate analysis and weather forecasting. Most zenith tropospheric delay (ZTD) models are presently used as positioning corrections, and few models are used for the estimation of water vapor, especially in Antarctica. Through two blind source separation algorithms (principal component analysis (PCA) and independent component analysis (ICA)), a back-propagation (BP) neural network and a deep learning technique (long short-term memory (LSTM) network), we establish an hourly high-accuracy ZTD model for GPS meteorology using the GPS-ZTD from 52 GPS stations in West Antarctica. Our results show that under the condition in which the principal components (PCs) and independent components (ICs) remain fixed after decomposition, the mean accuracy of the models for West Antarctica using PCA or ICA are better than 10 mm. Compared with the ZTDs from the nonmodeling stations, the mean root mean square (RMS) of the PCA and ICA models are 9.3 and 8.9 mm, respectively, and the correlation coefficients between the GPS-ZTD and model-ZTDs all exceed 90%. The accuracy of the ICA model is slightly higher than that of the PCA model, and the ICs of the ICA model show more consistent spatial responses. The six-hour forecast is the best among the forecast results, with a mean correlation coefficient of 90.6% and a mean RMS of 7.2 mm using GPS-ZTD. The long-term forecast result is significantly inaccurate, as the correlation coefficient between the 24-h forecast and GPS-ZTD is only 63.2%. Generally modest results have been achieved (HSS ≤ 0.38). Furthermore, the forecast accuracy in coastal areas is lower than that in inland areas. Our study confirms that the combined use of ICA and deep learning in ZTD modeling can effectively restore the original signals, and short-term forecasting can be effectively used in GPS meteorology. However, further development of the technology is necessary.

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AFRC-Trop: New Real-Time Zenith Tropospheric Delay Model over Africa

Abdelazeem

2021

J. Surv. Eng.

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Regional spatio-temporal zenith tropospheric delay modelling using independent component analysis

Cited by 3 publications

References 25 publications

A method for correcting InSAR interferogram errors using GNSS data and the K-means algorithm

A method for correcting InSAR interferogram errors using GNSS data and the K-means algorithm

Modeling and Forecasting the GPS Zenith Troposphere Delay in West Antarctica Based on Different Blind Source Separation Methods and Deep Learning

AFRC-Trop: New Real-Time Zenith Tropospheric Delay Model over Africa

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