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September 11, 2026
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The Development of a Respiration Signal Detecting Algorithm Exploiting Cyclostationary Properties

P. 1–5.
Shevgunov T.

The paper presents an algorithm for processing secondary radar signals that is based on identification of the characteristic cyclic frequencies specific to the breathing signals of a motionless human. The main procedure of the algorithm consists in sequential processing of signals contained in the range lines of a radar frame. It includes pre-processing to remove low-frequency offset and high-frequency noise, generating an estimate of the spectral correlation function and calculating pseudo-power based on it, and selecting cyclic frequencies exceeding a variable threshold. The operation of the algorithm is demonstrated using experimental data obtained using a radar system emitting signals with step frequency modulation. The proposed algorithm can be used in the development of new and modernization of existing technical solutions, such as radar systems for non-contact monitoring of the health conditions, highly specialized radars detecting survivors in rubble or electronic aids for people with disabilities.

Language: English
DOI
Text on another site
Keywords: Cyclostationarityspectral correlation functioncyclostationary processradar signal processingvital signsrespiration detectionCFAR detection

In book

2025 Systems of Signals Generating and Processing in the Field of on Board Communications
IEEE, 2025.
Similar publications
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Shevgunov T., , in: 2024 Systems of signals generating and processing in the field of on board communications.: IEEE, 2024. P. 1–5.
The paper is aimed at investigating the difference between different forms of time-varying autocorrelation function (TVACF) used for the quantitative expression of the second-order statistical properties exhibiting by non-stationary random processes. The generalized form of TVACF is proposed where the position of the current time moment can be set by means of additional parameter. The ...
Added: February 25, 2026
Алгоритм оценки спектральной корреляционной функции с использованием двумерного быстрого преобразования Фурье
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An algorithm for estimating the spectral correlation function of cyclostationary random processes on the basis of their finite-time realization is proposed. The main algorithm steps are described and the main operations performed at each of them are formalized. The presented estimates of the spectral correlation function in the presence of a correlated stationary noise overlapping ...
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This chapter presents the algorithm for estimating spectral correlation function of a random process that is a valid bi-frequency description of the probabilistic properties of any wide-sense cyclostationary process and relates to its cyclic autocorrelation function via Fourier transform. The key point of the algorithm is that it is based on the two-dimensional discrete Fourier transform of the sample ...
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Averaged Absolute Spectral Correlation Density Estimator
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Added: April 1, 2019
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