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Abstract <p>An algorithm for nonparametric amplitude detection of signals with an extended spectrum, including the signal-to-noise ratio (SNR) and the possibility of signal selection, was implemented and evaluated in the GNU Radio Companion environment. Numerical simulations were carried out using two signals with frequency-hopping spectrum-spreading (FHSS), distorted by Gaussian noise sequences, the synthesis of which was implemented as a separate part of the study. The simulation and measurement results have confirmed the possibility of using the proposed approach to detect the direction of a broadband signal source under the conditions of low SNR and in the presence of interference. Improved selective capabilities of the implemented algorithm have been achieved. During the development of the algorithm, an approach of using a sequence of simple mathematical transformations was chosen, which enabled us to reduce the computational costs of its operation.</p>

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Nonparametric Amplitude Method for Detecting FHSS Signals with Low Computational Costs

  • 期刊论文

  • 发表日期：

    2025年1月1日

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  • Igor Kovalenko,
  • Andrii Movchaniuk,
  • Yana Zinher,
  • Volodymyr Adamenko

摘要

Abstract

An algorithm for nonparametric amplitude detection of signals with an extended spectrum, including the signal-to-noise ratio (SNR) and the possibility of signal selection, was implemented and evaluated in the GNU Radio Companion environment. Numerical simulations were carried out using two signals with frequency-hopping spectrum-spreading (FHSS), distorted by Gaussian noise sequences, the synthesis of which was implemented as a separate part of the study. The simulation and measurement results have confirmed the possibility of using the proposed approach to detect the direction of a broadband signal source under the conditions of low SNR and in the presence of interference. Improved selective capabilities of the implemented algorithm have been achieved. During the development of the algorithm, an approach of using a sequence of simple mathematical transformations was chosen, which enabled us to reduce the computational costs of its operation.