Multidimensional visualization analysis based on large-scale GNSS data

Pub Date : 2024-03-19 DOI:10.1515/astro-2022-0037
Jingyan Wang, Ronghui Wang, Zhenyong Bo, Hengnian Li, Chong Wang, Yanan Fang
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Abstract

With the deployment of global navigation systems such as GPS, GLONASS, GALILEO, and BeiDou, and the construction of the global observation network, global navigation satellite system (GNSS) data have greatly expanded. Traditional relational databases and file systems can no longer efficiently store and process GNSS data. In addition, multidimensional, in-depth visual analysis methods for such data are lacking. In this paper, we provide a solution and implement a GNSS data visualization system based on MapV and cesium running on the Hadoop platform, which can effectively solve the problems of the lack of storage and computing resources for these massive multisource heterogeneous data. The proposed system provides multidimensional presentations to show how the space and ground segments of the entire system are organized by analyzing GNSS data.
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基于大规模全球导航卫星系统数据的多维可视化分析
随着 GPS、GLONASS、GALILEO 和北斗等全球导航系统的部署和全球观测网络的建设,全球导航卫星系统(GNSS)数据大大增加。传统的关系数据库和文件系统已无法有效地存储和处理 GNSS 数据。此外,对此类数据缺乏多维、深入的可视化分析方法。本文提供了一种解决方案,并实现了基于 MapV 和铯的 GNSS 数据可视化系统,该系统运行在 Hadoop 平台上,可有效解决这些海量多源异构数据缺乏存储和计算资源的问题。所提出的系统通过分析 GNSS 数据,提供多维度的演示,展示整个系统的空间段和地面段是如何组织的。
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