Abstract

Contributed Talk - Splinter DataManage

Thursday, 12 September 2024, 15:25   (S22)

Classical theory of the optimal filtering in context of radio astronomy

Vladimir Lenok
Bielefeld University

Radio astronomy offers large discovery potential and operates with substantial volumes of data and high-rate data streams. In contrast to the other fields facing similar data-related challenges, not all data in radio astronomy contain useful scientific information due to the unavoidable presence of noise in the data. That problem of efficient detection of signals in presence of noise has already been extensively studied in the context of statistical signal processing for radars and sonars. The solution to this problem forms the foundation of the classical theory of optimal filtration which provides a clear mathematical framework for signal processing methods that attain the minimal possible detection threshold and, in this sense, harvest the useful information from the data in the most efficient manner. Despite these advances, this theory has received little attention in the context of radio astronomy. The talk will provide an overview of the classical theory of optimal filtration and demonstrate its applicability in the development of efficient data analysis methods for current and future generations of radio astronomy instruments.