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- Title
Separation of Spacecraft Noise From Geomagnetic Field Observations Through Density‐Based Cluster Analysis and Compressive Sensing.
- Authors
Hoffmann, Alex Paul; Moldwin, Mark B.
- Abstract
The use of magnetometers for space exploration is inhibited by magnetic noise generated by spacecraft electrical systems. Mechanical booms are traditionally used to extend magnetometers away from noise sources. If a spacecraft is equipped with multiple magnetometers, signal processing algorithms can be used to compare magnetometer measurements and remove stray magnetic noise signals. We propose the use of density‐based cluster analysis to identify spacecraft noise signals and compressive sensing to separate spacecraft noise from geomagnetic field data. This method assumes no prior knowledge of the number, location, or amplitude of noise signals, but assumes that they have minimal overlapping spectral properties. We demonstrate the validity of this algorithm by separating high latitude magnetic perturbations recorded by the low‐Earth orbiting satellite, SWARM, from noise signals in simulation and in a laboratory experiment using a mock CubeSat apparatus. In the case of more noise sources than magnetometers, this problem is an instance of underdetermined blind source separation (UBSS). This work presents a UBSS signal processing algorithm to remove spacecraft noise and minimize the need for a mechanical boom. Plain Language Summary: Magnetometers are instruments designed to measure magnetic fields. They are used for a variety of purposes such as monitoring the magnetic field of the Earth from spacecraft. Spacecraft systems such as solar panels and reaction wheels generate magnetic noise that interferes with magnetometer readings. If the spacecraft has multiple magnetometers, each noise source will have a different magnitude at each magnetometer depending on the location of the noise source. The system which describes the magnitude of each noise source at each magnetometer is called a mixing matrix. We propose the use of unsupervised machine learning to estimate the mixing matrix. Once the mixing matrix is estimated, the Earth's magnetic field can be separated from spacecraft magnetic noise using a method called Compressive Sensing. Spacecraft often have many more noise sources than magnetometers, which complicates noise cancellation. The proposed method has the ability to clean noisy magnetometer measurements when there are more noise signals present than magnetometers. Key Points: We present the first use of compressive sensing with cluster analysis to separate spacecraft noise from geomagnetic field dataWe demonstrate the separation of wideband noise signals in simulation and in a lab experiment using SWARM residual geomagnetic field dataThe method enables accurate magnetic field measurements from resource limited and magnetically noisy spacecraft such as boomless CubeSats
- Subjects
GEOMAGNETISM; CLUSTER analysis (Statistics); MAGNETIC field measurements; BLIND source separation; SPACE vehicles; MAGNETIC noise; SPACE exploration
- Publication
Journal of Geophysical Research. Space Physics, 2022, Vol 127, Issue 9, p1
- ISSN
2169-9380
- Publication type
Article
- DOI
10.1029/2022JA030757