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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.
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