Rapid troposphere tomography using adaptive simultaneous iterative reconstruction technique

Zhang, Weixing; Lou, Yidong; Liu, Wenxuan; Huang, Jiansheng; Wang, Zhipeng; Zhou, Yaozong; Zhang, Haoshan

doi:10.1007/s00190-020-01386-4

Cited by 24 publications

(10 citation statements)

References 37 publications

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“…For GNSS processing, the GNSS data with the sampling rate of 30 s from the two networks during the period DOY 219-243, 2017, when both regions are in summer and often suffer from rainstorms, are processed, using GAMIT/GLOBK software. The cut-off angle for tropospheric parameters estimation applied here is 10° (Zhang et al 2020a). Besides, three International GNSS Service (IGS) stations (BJFS, SHAO, and LHAZ in Fig.…”

Section: Experiments Setupmentioning

confidence: 99%

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

Zhang

Zhang²,

Chang³

et al. 2021

J Geod

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Accurate three-dimensional (3D) atmospheric water vapor distribution, which plays a crucial role in understanding the meteorological phenomena and hazards, has been successfully retrieved using Global Navigation Satellite System (GNSS) tomography technique. Presently, the problem of the ill-posed tomography system, that results from poor GNSS acquisition geometry, remains a vital issue to be solved. In this paper, we develop a new hybrid observation GNSS tomography (HOGT) method, which constructs and introduces the virtual signals, inverted to the real rays, to address the acquisition geometry defect. Within the HOGT, the slant wet delay (SWD) of the virtual inverted signal (VIS) is estimated by means of the tropospheric parameters derived from the hourly ERA5 data using the ray-tracing algorithm. Two designed experiments, based on the dense and sparse GNSS networks (corresponding to Hong Kong and Xuzhou), respectively, are implemented to assess the performance of HOGT for the different networks. The results reveal that HOGT provides a more robust observation geometry and more accurate water vapor distribution than the traditional tomography model, with the mean number of the crossed voxels enhanced by 26.45% and 27.11% for the two networks, and the average root-mean-square error (RMSE) of the tomography solutions improved by 18.18% and 38.28% in the two areas, respectively. Furthermore, HOGT shows a significant improvement close to the Erath's surface from 0 to 2 km, implying its superior capability to optimize the accuracy of tomography results. An additional experiment to investigate the performance of the proposed method under different time resolutions demonstrates that HOGT can be promised to retrieve more accurate water vapor distribution over short time intervals, especially for rainy days with an interval of 10 min or even shorter, which highlights the interest in tomography solutions for improving the understanding of severe weather. KeywordsGlobal Navigation Satellite System (GNSS) • Hybrid observation GNSS tomography (HOGT) • Virtual inverted signals (VIS) • Dense and sparse networks • ERA5 • Radiosonde B Shubi Zhang

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Section: Experiments Setupmentioning

confidence: 99%

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

Zhang

Zhang²,

Chang³

et al. 2021

J Geod

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“…Station coordinates were estimated as daily constants. The cutoff elevation angle of satellites was set to 7 • , and an elevation-dependent weighting strategy was applied [40]. The precision index of the estimated ZTDs output by the software was used for further designing the WRFDA assimilation weighting strategies.…”

Section: Gps Data Processingmentioning

confidence: 99%

On the Assessment GPS-Based WRFDA for InSAR Atmospheric Correction: A Case Study in Pearl River Delta Region of China

et al. 2021

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The accuracy and applications of synthetic aperture radar interferometry (InSAR) are severely suppressed by tropospheric error. Numerical Weather Models (NWMs) and GPS-derived tropospheric delays have been widely used to correct the tropospheric error considering their complete spatial coverage or high accuracy. However, few studies focus on the fusion of both NWMs and GPS for the tropospheric error correction. In this study, we used the Weather Research and Forecasting (WRF) to obtain NWMs with a higher spatial-temporal resolution of 3 km and 20 s from both ERAI (79 km and 6 h) and ERA5 (0.25° and 1 h). After that, we utilized the WRF Data Assimilation (WRFDA) system to assimilate the GPS ZTD into these enhanced NWMs and generate merged NWMs products. The tropospheric correction effectiveness from different NWMs products was evaluated in a case in the Pearl River Delta region of China. The results showed that all the NWMs products could correct the stratified component in the interferogram but could not mitigate the turbulence well, even after improving the spatial-temporal resolution. As for the trend component, the merged NWMs products showed obvious superiority over other products. From the statistics perspective, the stdev of the interferogram decreased further over 20% by the merged NWMs products than other products when using both ERAI and ERA5, indicating the significant effectiveness of GPS ZTD assimilation.

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“…To solve the above mentioned ill-posed inverse problem, various tomographic methods have been proposed by scholars around the world, among which the algebraic iterative reconstruction (AIR) methods have been widely used [11], [17]− [19] for their advantages of avoiding complicated matrix inversion and saving computational cost. The two types of the AIR methods are sequential and simultaneous versions, namely algebraic reconstruction techniques (ARTs) [20] and simultaneous iterative reconstruction techniques (SIRTs) [21].…”

Section: Introductionmentioning

confidence: 99%

A Two-Step Projected Iterative Algorithm for Tropospheric Water Vapor Tomography

Liu

Zhang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The tropospheric tomography is an ill-posed inversion problem due to the sparsity of Global Navigation Satellite Systems (GNSS) stations and the limitation on the projection angles of GNSS signals, which in turn affects the stability and robustness of the tomographic solution. To address this, a new tomographic algorithm, named two-step projected iterative algorithm (TSPIA), is proposed. The wet refractivity (WR) field was constructed in two steps: first, an iterative preprocessing for the initial input values was performed, then its resultant solution was input into the projected iterative method, in which a hypothesis convex set was constructed to constrain the reconstruction based on the classical algebraic iterative reconstruction (AIR) methods. In addition, a two-dimensional normalized cumulative periodogram (2D-NCP) termination criterion was investigated since the traditional criteria for judging the convergence of iterations use pre-fixed empirical thresholds, which may lead to excessive iterations and need complicated work. The TSPIA was tested using GNSS data in Hong Kong over a wet period and a dry period. Statistical results showed that, compared to the classical AIR methods, the accuracy of the reconstructed WR field of the TSPIA were improved by about 10% and 15% when radiosonde and ECMWF data were used as the reference, respectively. Moreover, experiments for the proposed 2D-NCP criterion demonstrated noticeable computational efficiency. These results suggest that the new approaches proposed in this study can improve the performance of the iterative methods for GNSS tropospheric tomography.

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Rapid troposphere tomography using adaptive simultaneous iterative reconstruction technique

Cited by 24 publications

References 37 publications

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

On the Assessment GPS-Based WRFDA for InSAR Atmospheric Correction: A Case Study in Pearl River Delta Region of China

A Two-Step Projected Iterative Algorithm for Tropospheric Water Vapor Tomography

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