The Askaryan Radio Array (ARA), located near the geographical South Pole, is among the first experiments at the South Pole designed to detect ultra-high energy neutrinos through the Askaryan effect. When such neutrinos interact within dense media such as ice, they initiate particle cascades that, as they evolve, generate coherent radio pulses. Operating in the 150–850 MHz frequency band, ARA is deployed 80–200 meters deep in Antarctic ice, where the radio frequency background is exceptionally low. Despite the low background, experiments such as ARA must still account for continuous wave (CW) signals, which can originate from anthropogenic sources, instrumental noise, and other environmental factors. These CW signals can potentially obscure the faint neutrino-induced radio pulses, complicating data analysis and event identification. Over the years, ARA has developed and refined a number of techniques for CW filtering and identification, including spectral analysis, notch filtering, and phase-variance methods. These approaches exploit the unique characteristics of CW signals, such as their narrowband nature and temporal persistence, to effectively separate CW contamination from genuine impulsive events. We review the main CW identification and filtering techniques developed within the ARA collaboration and present recent improvements in their adaptive, multi-stage filtering pipelines. These advances have led to faster processing, easier operation, and more accurate CW identification and suppression, improving the consistency and quality of data analysis. The efficacy of these methods is demonstrated through CW identification and filtering for all ARA stations, showcasing their critical role in reducing event misclassification and improving the experiment's overall performance. By refining these techniques, this work not only improves the sensitivity and data analysis performance of ARA, but also underscores the importance of robust CW identification and filtering for current and future neutrino radio detection experiments.
Seikh et al. (Wed,) studied this question.