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

Finley, Matthew G.; Flores, Allison M.; Morris, Katherine J.; Broadfoot, Robert M.; Hisel, Sam; Homann, Jason; Piker, Chris; Sen Gupta, Ananya; Miles, David M.

doi:https://doi.org/10.5194/gi-13-263-2024

Articles | Volume 13, issue 2

https://doi.org/10.5194/gi-13-263-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gi-13-263-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 2

Research article

|

20 Aug 2024

Research article |

| 20 Aug 2024

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

Matthew G. Finley, Allison M. Flores, Katherine J. Morris, Robert M. Broadfoot, Sam Hisel, Jason Homann, Chris Piker, Ananya Sen Gupta, and David M. Miles

Data sets

Code and Data for Enabling In-Situ Magnetic Interference Mitigation Algorithm Validation via a Laboratory-Generated Dataset Matthew G. Finley et al. https://doi.org/10.25820/data.007168

Short summary

Spaceflight magnetic-field measurements are often contaminated by interference from the host spacecraft. We present a new dataset to enable the development and testing of interference mitigation schemes for spaceflight magnetic-field data. Over 100 h of data, including laboratory-generated proxies for magnetic interference and geophysical signals, have been produced. A ground truth for the underlying interference is also provided, enabling the rigorous quantification of data-cleaning techniques.