asteRisk - Integration and Analysis of Satellite Positional Data in R

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
R Journal Pub Date : 2023-08-26 DOI:10.32614/rj-2023-023
Rafael Ayala, Daniel Ayala, Lara Sellés Vidal, David Ruiz
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引用次数: 0

Abstract

Over the past few years, the amount of artificial satellites orbiting Earth has grown fast, with close to a thousand new launches per year. Reliable calculation of the evolution of the satellites' position over time is required in order to efficiently plan the launch and operation of such satellites, as well as to avoid collisions that could lead to considerable losses and generation of harmful space debris. Here, we present asteRisk, the first R package for analysis of the trajectory of satellites. The package provides native implementations of different methods to calculate the orbit of satellites, as well as tools for importing standard file formats typically used to store satellite position data and to convert satellite coordinates between different frames of reference. Such functionalities provide the foundation for integrating orbital data and astrodynamics analysis in R.
asteRisk -卫星位置数据的集成与分析
在过去几年中,绕地球运行的人造卫星数量增长迅速,每年发射近1000颗新卫星。需要可靠地计算卫星位置随时间的演变,以便有效地规划这类卫星的发射和运行,并避免可能导致相当大损失和产生有害空间碎片的碰撞。在这里,我们介绍asteRisk,第一个用于分析卫星轨迹的R包。该软件包提供了计算卫星轨道的不同方法的本机实现,以及用于导入通常用于存储卫星位置数据和在不同参照系之间转换卫星坐标的标准文件格式的工具。这些功能为在R中集成轨道数据和天体动力学分析提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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