Aaron Nielsen
Selected Presentations and Publications
Presentations
Canciani, A., & Nielsen, A. (2023). Absolute positioning using magnetic anomaly fields: An introduction to the technique and a summary of extensive ongoing development of aircraft, surface ship, and sub-surface ship navigation systems utilizing earth magnetic anomaly fields to navigate. (Invited) GP32A-03 (GP32A-03). AGU 2023. Nielsen, A. (2023). Machine learning for magnetic anomaly navigation. Presented at Wright-Brothers Insitute AI/ML Collider Event. https://afit-eeng-magnav.github.io/2023-05-17-wbi-collider/ Nielsen, A. (2023). 2023 PLANS MagNav tutorial. Tutorial presentation at IEEE/ION PLANS 2023. https://afit-eeng-magnav.github.io/2023-PLANS-MagNav-Tutorial/ Nielsen, A., & Saltus, R. (2023). MagNav workshop. Workshop presentations at IEEE/ION PLANS 2023. https://afit-eeng-magnav.github.io/2023-PLANS-MagNav-Workshop/ Nielsen, A. (2022). Machine learning for magnetic navigation. Presented at September Meeting of Gem City Tech Machine Learning Group. https://gemcityml.com/magnav_contest/
Press releases
Publications
Lathrop, F. W., Taylor, C. N., & Nielsen, A. P. (2024). Magnetic sensor compensation using factor graph estimation. IEEE Sensors Journal, 24(15), 23711–23722. https://doi.org/10.1109/JSEN.2024.3416618 Moradi, M., Zhai, Z.-M., Nielsen, A., & Lai, Y.-C. (2024). Random forests for detecting weak signals and extracting physical information: A case study of magnetic navigation. APL Machine Learning, 2(1). https://doi.org/10.1063/5.0189564 Gnadt, A. R., Wollaber, A. B., & Nielsen, A. P. (2022). Derivation and extensions of the tolles-lawson model for aeromagnetic compensation. arXiv. https://doi.org/10.48550/ARXIV.2212.09899 Gnadt, A. R., Belarge, J., Canciani, A., Carl, G., Conger, L., Curro, J., Edelman, A., Morales, P., Nielsen, A. P., O’Keeffe, M. F., Rackauckas, C. V., Taylor, J., & Wollaber, A. B. (2020). Signal enhancement for magnetic navigation challenge problem. arXiv. https://doi.org/10.48550/ARXIV.2007.12158