Title
Node-Based Optimization of GNSS Tomography with a Minimum Bounding Box Algorithm.
Abstract
Global Navigation Satellite Systems (GNSS) tomography plays an important role in the monitoring and tracking of the tropospheric water vapor. In this study, a new approach for improving the node-based GNSS tomography is proposed, which makes a trade-off between the real observed region and the complexity of the discretization of the tomographic region. To obtain dynamically the approximate observed region, the convex hull algorithm and minimum bounding box algorithm are used at each tomographic epoch. This new approach can dynamically define the tomographic model for all types of study areas based on the GNSS data. The performance of the new approach is tested by comparing it against the common node-based GNSS tomographic approach. Test data in May 2015 are obtained from the Hong Kong GNSS network to build the tomographic models and the radiosonde data as a reference are used for validating the quality of the new approach. The experimental results show that the root-mean-square errors of the new approach, in most cases, have a 38 percent improvement and the values of standard deviation reduce to over 43 percent compared with the common approach. The results indicate that the new approach is applicable to the node-based GNSS tomography.
Year
DOI
Venue
2020
10.3390/rs12172744
REMOTE SENSING
Keywords
DocType
Volume
GNSS,tomographic technique,water vapor,minimum bounding box
Journal
12
Issue
Citations 
PageRank 
17
0
0.34
References 
Authors
0
11
Name
Order
Citations
PageRank
Nan Ding112730.26
Xiangrong Yan200.34
Shubi Zhang300.34
suqin wu453.40
Xiaoming Wang55712.72
Yang Zhang610422.94
Yu-Chen Wang73427.05
Xin Liu822128.53
Wenyuan Zhang997.21
Lucas Holden1051.98
Kefei Zhang115218.45