This research demonstrates a CFAR approach to detect harmonic components in acoustic signals, improving detection in variable background noise.
The article is devoted to the detection of harmonic components in the acoustic signal spectrum of propeller aerial attack weapon. The received acoustic signal may contain harmonics of both one and several radiation sources. By analyzing the frequency values of the harmonic components with regard to the Doppler shift and their distribution along the frequency axis, it is possible to determine the number of radiation sources and estimate their motion parameters. Detecting harmonic components in the background noise is difficult because its spectral density is uneven and unknown. To solve this problem, it is proposed to use an adaptive thresholding method, an algorithm with a constant false alarm rate, which is used to detect radar signals, as it is able to track changes in noise levels. The spectrum of the acoustic signal is analyzed and the numerical values of the parameters necessary for tuning the algorithm are determined. A comparison was made between three different approaches to assessing background noise levels and calculating detection thresholds, including cell averaging-, smallest-of cell averaging-, and order statistics- constant false alarm rate. The parameters of the algorithm have been determined, which allow us to build a threshold that provides tracking of noise level changes and detection of both strong and weak harmonics in the spectrum of an acoustic signal. The experimental results show that the proposed method allows detecting 45% more harmonics compared to the consecutive mean excision algorithm and 26% more harmonics compared to the moving average algorithm. The results obtained can be used to improve existing and develop new devices and systems for acoustic monitoring of airspace.
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V. Pozdniakov (2025) studied this question.
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