风淋探测自触发天线簇效率估计

P. Bezyazeekov, O. Fedorov, Y. Kazarina, O. Kopylova, D. Kostunin, V. Lenok, S. Malakhov
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引用次数: 3

摘要

气淋阵无线电阵列在低信噪比条件下工作,这使得气淋阵信号的自主测量变得复杂,而不使用来自光学或闪烁探测器的外部触发。无线电探测器的简单阈值触发器只能有效地应用于无线电安静条件,因为在其他情况下,该触发器检测到高比例的噪声脉冲。在本工作中,我们研究了具有复杂实时触发系统的密集天线簇独立风淋探测的各个方面。为了选择实时分析的最佳程序,我们研究了触发效率、计数率、检测器硬件和几何之间的依赖关系。在本研究中,我们开发了一个框架,用于测试各种规格阵列的各种信号检测和噪声过滤方法,以及基于现场可编程门阵列的这些方法的硬件实现。该框架为检测信号的站级和集群级步骤的管理提供了灵活的设置,优化了实时处理的硬件实现。它包括用于初始配置和对预记录数据进行测试的数据处理工具、用于配置触发架构的工具以及用于在给定宇宙射线能量和空气淋浴脉冲幅度阈值下初步估计触发效率的工具。我们展示了使用该框架开发的触发器管道的示例,并讨论了对模拟数据的测试结果。
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Efficiency estimation of self-triggered antenna clusters for air-shower detection
Air-shower radio arrays operate in low signal-to-noise ratio conditions, which complicates the autonomous measurement of air-shower signals without using an external trigger from optical or scintillator detectors. A simple threshold trigger for radio detector can be efficiently applied onlyin radio-quiet conditions, because for other cases this trigger detects a high fraction of noise pulses. In the present work, we study aspects of independent air-shower detection by dense antenna clusters with a complex real-time trigger system. For choosing the optimal procedures for the real-time analysis, we study the dependence between trigger efficiency, count rate, detector hardware and geometry. For this study, we develop a framework for testing various methods of signal detection and noise filtration for arrays with various specifications and the hardware implementation of these methods based on field programmable gate arrays. The framework provides flexible settings for the management of station-level and cluster-level steps of detecting the signal, optimized for the hardware implementation for real-time processing. It includes data-processing tools for the initialconfiguration and tests on pre-recorded data, tools for configuring the trigger architecture andtools for preliminary estimates of the trigger efficiency at given thresholds of cosmic-ray energyand air-shower pulse amplitude. We show examples of the trigger pipeline developed with this framework and discuss the results of tests on simulated data.
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