Enabling in situ validation of mitigation algorithms for magnetic interference via a laboratory-generated dataset

Abstract

Magnetometer measurements are one of the critical components necessary for improving 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 require the application of interference mitigation algorithms prior to scientific use. Rigorous numerical validation of these techniques can be challenging when the techniques are applied to in situ spaceflight data as a ground truth for the local magnetic field is often unavailable. This paper 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 h of magnetic-field data, comprising mixtures of near-direct-current (near-DC) trends, physically synthesized interference, and pseudo-geophysical phenomena. These constituent source signals have been independently captured by four synchronized magnetometers sampling at a high cadence and combined into 30 min intervals of data representing events and interference seen in historic missions. The physical locations of the four magnetometers relative to the interference sources enable 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 the rigorous quantification of the results of past, present, and future interference mitigation efforts.