Enabling In-Situ Magnetic Interference Mitigation Algorithm Validation via a Laboratory-Generated Dataset

IF 1.8 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Matthew G. Finley, Allison M. Flores, Katherine J. Morris, Robert M. Broadfoot, Sam Hisel, Jason Homann, Chris Piker, Ananya Sen Gupta, David M. Miles
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引用次数: 0

Abstract

Abstract. Magnetometer measurements are one of the critical components necessary to improve our understanding of the intricate physical processes coupling mass, momentum, and energy within near-Earth space and throughout our solar system. However, these measurements are often contaminated by stray magnetic fields from the spacecraft hosting the magnetic field sensors, and the data often requires the application of interference mitigation algorithms prior to scientific use. Rigorous numerical validation of these techniques can be challenging when they are applied to in-situ spaceflight data, as a ground truth for the local magnetic field is often unavailable. This manuscript introduces and details the generation of an open-source dataset designed to facilitate the assessment of interference mitigation techniques for magnetic field data collected during spaceflight missions. The dataset contains over 100 hours of magnetic field data comprising mixtures of near-DC trends, physically-synthesized interference, and pseudo-geophysical phenomena. These constituent source signals have been independently captured by four synchronized magnetometers sampling at high cadence and combined into 30-minute intervals of data representative of events and interference seen in historic missions. The physical location of the four magnetometers relative to the interference sources enables researchers to test their interference mitigation algorithms with various magnetometer suite configurations, and the dataset also provides a ground truth for the underlying interference signals, enabling rigorous quantification of the results of past, present, and future interference mitigation efforts.
通过实验室生成的数据集实现原位磁干扰缓解算法验证
摘要。磁强计测量是提高我们对近地空间和整个太阳系内质量、动量和能量耦合的复杂物理过程的理解所必需的关键组成部分之一。然而,这些测量往往会受到磁场传感器所在航天器的杂散磁场的污染,数据在科学使用之前往往需要应用干扰缓解算法。当这些技术应用于原位空间飞行数据时,对其进行严格的数值验证具有挑战性,因为通常无法获得当地磁场的地面实况。本手稿介绍并详细说明了一个开源数据集的生成过程,该数据集旨在促进对太空飞行任务期间收集的磁场数据进行干扰缓解技术评估。该数据集包含 100 多个小时的磁场数据,包括近直流趋势、物理合成干扰和伪地球物理现象的混合物。这些组成源信号由四个同步磁强计以高节奏采样独立捕获,并合并成 30 分钟间隔的数据,这些数据代表了历史任务中出现的事件和干扰。四个磁强计相对于干扰源的物理位置使研究人员能够利用各种磁强计套件配置测试其干扰缓解算法,该数据集还为基本干扰信号提供了地面实况,从而能够对过去、现在和未来的干扰缓解工作的结果进行严格量化。
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来源期刊
Geoscientific Instrumentation Methods and Data Systems
Geoscientific Instrumentation Methods and Data Systems GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
3.70
自引率
0.00%
发文量
23
审稿时长
37 weeks
期刊介绍: Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following: concepts, design, and description of instrumentation and data systems; retrieval techniques of scientific products from measurements; calibration and data quality assessment; uncertainty in measurements; newly developed and planned research platforms and community instrumentation capabilities; major national and international field campaigns and observational research programs; new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters; networking of instruments for enhancing high temporal and spatial resolution of observations. GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following: foster scientific discussion; maximize the effectiveness and transparency of scientific quality assurance; enable rapid publication; make scientific publications freely accessible.
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