Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques
Qiutong Jin, Ananya Sen Gupta, Mirela Kapo, Emma Hawk, Jasper S. Halekas
Abstract
We propose a novel "big data" application of geometric feature extraction techniques to autonomously identify and track the temporal evolution of charged particle trails in the Martian ionosphere. Specifically, we propose a Radon-transform extension to the geometric distance transform to algorithmically isolate potentially overlapping trail features in energy spectrograms. Our methods seek to connect large- scale statistical analysis with individual case studies and thus provide the computational framework or connecting theoretical models with potential terabytes of remote sensing data. Based on individual ion populations as the basic unit of observation, we provide data-driven results of applying our method over representative energy spectrograms generated from the NASA Mars Atmosphere and Volatile Evolution (MAVEN) mission data from the Solar Wind Ion Analyzer (SWIA) instrument.
BibTeX
@inproceedings{icassp2019_autonomousdetect,
title = {Autonomous Detection and Disambiguation of Martian Ion Trails Using Geometric Signal Processing Techniques},
author = {Qiutong Jin and Ananya Sen Gupta and Mirela Kapo and Emma Hawk and Jasper S. Halekas},
booktitle = {ICASSP 2019},
year = {2019}
}