An Automatic Method for Detection and Naive Classification of the Martian Ionospheric Irregularities

The abundant observations and research established a detailed category of the terrestrial ionospheric irregularities, which significantly advanced our understanding of how the Earth system's complicated physical and chemical process generates the intermediate-scale structures of the charged particles. Motivated by a future attempt at categorizing the Martian ionospheric irregularity, this study designs a method for naive classification of the plasma density depletion, enhancement, and oscillation based on the in situ measurements of the Martian ionosphere. The technique consists of several procedures: trend estimation, detrending and candidate extraction, and parameterization. The classification is achieved through a machine-learning-like process using some testing artificial density profiles. A preliminary credence test shows a good performance in separating the terrestrial low-latitude Equatorial Plasma bubble (depletion) and mid-latitude Median-scale Traveling Ionospheric Disturbance (oscillation). Another detection experiment of the Martian plasma depletion events (collected by Basuvaraj et al. (2022a, )) showed a recall rate (i.e., true positive) of 38% but with a high precision of 67.8%. Therefore, we believe the proposed method could convincingly extract different Martian ionospheric irregularities and help uncover the climatological characteristics in the future. Ionospheric irregularities refer to the inhomogeneous distribution of the charged particles in the ionosphere, which would affect radio wave transmission and thus pose threats to tremendous human-made assets deployed in terrestrial outer space and on other planets such as Mars. Unlike the terrestrial ionospheric irregularities, whose categories and physical mechanisms are well-understood, the Martian counterparts are still in poor understanding. Previous studies have indicated the diversity, but the category has yet to be built. The large data set provided by the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission allows a more detailed investigation of the Martian ionospheric irregularities. Therefore, an automatic method to extract the ionospheric density enhancement, depletion, and oscillation would be a first step to figuring out the exact types of the Martian ionospheric irregularities, thus helping to extend our knowledge of how the finer ionospheric structures are formed backgrounded by the region crustal magnetic field other than the global dipole field. A modified rolling-barrel algorithm extracts the candidate irregularities Classification of the candidates into depletion, enhancement, and oscillation is achieved through a few parameterization processes Initial testing shows good performance on the Martian and terrestrial ionospheric irregularities