2020
DOI: 10.5194/gi-9-451-2020
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Maximum-variance gradiometer technique for removal of spacecraft-generated disturbances from magnetic field data

Abstract: Abstract. In situ measurement of the magnetic field using spaceborne instruments requires a magnetically clean platform and/or a very long boom for accommodating magnetometer sensors at a large distance from the spacecraft body. This significantly drives up the costs and the time required to build a spacecraft. Here we present an alternative sensor configuration and a technique allowing for removal of the spacecraft-generated AC disturbances from the magnetic field measurements, thus lessening the need for a m… Show more

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Cited by 20 publications
(23 citation statements)
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“…In order to monitor the perturbations from the station in more detail, several single magnetometer sensors will be mounted on various places directly on the station (Constantinescu et al, 2020). Additionally, we propose two current monitors, monitoring the currents flowing from the solar panels, which are expected to contribute the largest magnetic field perturbations.…”
Section: Cmagf: 3-axis Fluxgate Magnetometermentioning
confidence: 99%
“…In order to monitor the perturbations from the station in more detail, several single magnetometer sensors will be mounted on various places directly on the station (Constantinescu et al, 2020). Additionally, we propose two current monitors, monitoring the currents flowing from the solar panels, which are expected to contribute the largest magnetic field perturbations.…”
Section: Cmagf: 3-axis Fluxgate Magnetometermentioning
confidence: 99%
“…This approach proved highly effective for the 3U Ex-Alta 1 CubeSat (Miles et al, 2016). Active noise removal (e.g., Ness et al, 1971;Constantinescu et al, 2020) is also possible using an alternative gradiometer setup (e.g., two separated miniature sensors on the outer boom segment).…”
Section: Magnetic Cleanlinessmentioning
confidence: 99%
“…Constantinescu et al. (2020) use maximum variance analysis (MVA) to clean spacecraft magnetometer data. The MVA algorithm finds an orthogonal set of axes to maximize the variance of the measured signals.…”
Section: Introductionmentioning
confidence: 99%
“…BSS is the separation of a mixture of source signals without prior knowledge of the signal type or magnetometer location. Constantinescu et al (2020) use maximum variance analysis (MVA) to clean spacecraft magnetometer data. The MVA algorithm finds an orthogonal set of axes to maximize the variance of the measured signals.…”
mentioning
confidence: 99%