Background identification algorithm for future self-triggered air-shower radio arrays

TL;DR

This paper discusses progress in developing a self-trigger algorithm for radio detection of ultra-high energy air-showers, aiming to improve background resistance and enable large-scale detector deployment.

Contribution

It introduces a novel classification method for broadband pulses to enhance self-trigger technology in radio air-shower detectors.

Findings

Progress in broadband pulse classification for self-triggering.

Improved resistance to background noise in detection.

Potential for large-scale radio detector deployment.

Abstract

The study of the ultra-high energy cosmic rays, neutrinos and gamma rays is one of the most important challenges in astrophysics. The low fluxes of these particles do not allow one to detect them directly. The detection is performed by the measuring of the air-showers produced by the primary particles in the Earth's atmosphere. A radio detection of ultra-high energy air-showers is a cost-effective technique that provides a precise reconstruction of the parameters of primary particle and almost full duty cycle in comparison with other methods. The main challenge of the modern radio detectors is the development of efficient self-trigger technology, resistant to high-level background and radio frequency interference. Most of the modern radio detectors receive trigger generated by either particle or optical detectors. The development of the self trigger for the radio detector will significantly simplify the operation of existing instruments and allow one to access the main advantages of the radio method as well as open the way to the construction of the next generation of large-scale radio detectors. In the present work we discuss our progress in the solution of this problem, particularly the classification of broadband pulses.