Enhancing Magnetic Field Analysis on the KMAG Instrument: Applying WAIC‐UP for Spacecraft Interference Removal and Interpolating Data Gaps

The Korea Pathfinder Lunar Orbiter (KPLO) spacecraft utilizes the KPLO Magnetometer (KMAG) payload, a three‐fluxgate magnetometer array mounted on a 1.2 m boom, to measure crustal and induced lunar magnetic fields. The short boom length exposes the magnetometers to intricate, multi‐source stray magnetic fields. These interference signals include a low‐frequency, 20 nT peak‐to‐peak signal from the solar panels and batteries as the spacecraft transitions between sunlight and darkness during certain orbital phases. These stray magnetic fields impede the analysis of lunar magnetic anomalies with magnitudes up to 3 nT at a 100 km altitude. Additionally, downlink issues during the mission's initial stages occasionally resulted in data gaps of up to 12 min (approximately 13% of the orbit) in several orbits. To overcome these data quality challenges, we present a comprehensive three‐component method: (a) the Recurrent Forecasting Multichannel Singular Spectrum Analysis (M‐SSA) algorithm interpolates data gaps, (b) Wavelet‐Adaptive Interference Cancellation for Underdetermined Platforms (WAIC‐UP) removes stray magnetic fields from the continuous magnetometer measurements, and (c) the Removal Algorithm for Magnetometer Environmental Noise (RAMEN) gradiometry algorithm corrects low‐frequency trends not observed by WAIC‐UP. We demonstrate the efficacy of our approach by comparing the results with contemporaneous magnetic field measurements from the lunar‐orbiting ARTEMIS‐P1 spacecraft and lunar crustal magnetic field maps from the Lunar Prospector and Kaguya missions. This integrated application of M‐SSA, WAIC‐UP, and RAMEN enables KMAG to reliably investigate lunar magnetic fields despite non‐dipolar spacecraft interference and intermittent data gaps.