Ionospheric Observations from the ISS: Overcoming Noise Challenges in Signal Extraction

Abstract

The Electric Propulsion Electrostatic Analyzer Experiment (ÈPÈE) is a compact ion energy bandpass filter deployed on the International Space Station (ISS) in March 2023 and providing continuous measurements through April 2024. This period coincides with the Solar Cycle 25 maximum, capturing unique observations of solar activity extremes in the mid- to low-latitude regions of the topside ionosphere. From these in situ spectra we derive plasma parameters that inform space-weather impacts on satellite navigation and radio communication. We present a statistical processing pipeline for ÈPÈE that (i) estimates the instrument noise floor, (ii) accounts for irregular temporal sampling, and (iii) extracts ionospheric signals. Rather than discarding noisy data, the method learns a baseline noise model and fits the measurement surface using a scaled Vecchia Gaussian process approximation, recovering values typically rejected by thresholding. The resulting products increase data coverage and enable noise-assisted monitoring of ionospheric variability.

Figures (8)

• Figure 1: Distribution of current values across energy bins for a single timestamp (2023-09-29 00:33:18 UTC). Discrete current observations are marked by points and the underlying empirical distribution is fit with a line. Energy bin is on the x-axis and current is on the y-axis (nA) with color referring to energy value (eV). Energy value is discretized by bins; energy values increase as bin number increases. This is referenced with indigo blues fading to azure as energy value increases across the x-axis. Gray lines indicate the intersection of the maximum values for current and energy.
• Figure 2: Empirical distribution of current values across energy bins for a single timestamp (2023-09-28 23:05:20 UTC). Energy bin is on the x-axis and current is on the y-axis (nA). The increase in energy value (eV) is represented through a lightening blue color palette, with indigo blues indicating lower energy values and azure blues indicating higher energy values. In this instance, choosing a maximum value is not clear, and the majority of observations fall in close proximity to the actual maximum.
• Figure 3: Maximum current values (y-axis) across time (x-axis), with colors indicating respective current values. Cooler colors indicate lower current values and warmer colors indicate higher current values (range 0-5 nA). All observations with current values at or below the instrument noise floor (0.15 nA) are colored in dark grey. These current values often - although not always - occur in tandem with very high energy values.
• Figure 4: Flowchart depicting the methodology for handling values near the instrument noise floor. Inputs are in blue and outputs in burnt orange, both are rectangular shapes. Outputs that then become inputs in subsequent steps have a dashed outline. Processes are in purple circles with a solid line representing input to a process and an arrow representing output of a process. The final, desired variables of interest are identified with a white box outlined in black.
• Figure 5: Results of the noise profile fitting process for the first (top facet) and fourth quarter (bottom facet) of Julian day 271 (both with n=10799). Candidate noise timestamps (those identified as likely minimal signal) are plotted across energy bins (x-axis) and GP-smoothed current values (y-axis) with raw energy identified by coloring (blues lightening with increasing values). The final fitted noise profile, comprised of Richards and parabolic component shapes, is highlighted in red.