radioelectronicsИзвестия высших учебных заведений России. РадиоэлектроникаJournal of the Russian Universities. Radioelectronics1993-89852658-4794Saint Petersburg Electrotechnical University10.32603/1993-8985-2023-26-5-40-49radioelectronics-798Research ArticleРАДИОТЕХНИЧЕСКИЕ СРЕДСТВА ПЕРЕДАЧИ, ПРИЕМА И ОБРАБОТКИ СИГНАЛОВRADIO ELECTRONIC FACILITIES FOR SIGNAL TRANSMISSION, RECEPTION AND PROCESSINGParameter Justification of a Signal Recognition Algorithm Based on Detection at Two Intermediate FrequenciesParameter Justification of a Signal Recognition Algorithm Based on Detection at Two Intermediate Frequencieshttps://orcid.org/0000-0002-9222-2502NghiTran HuuNghiTran Huu

Tran Huu Nghi, Specialist in "Radioelectronic Systems and Complexes", Postgraduate Student. The author of 6 scientific publications

Department of Radio Electronic Means

Area of expertise: RF spectrum management

197022

5 F, Professor Popov St.

Saint Petersburg

Tran Huu Nghi, Specialist in "Radioelectronic Systems and Complexes", Postgraduate Student. The author of 6 scientific publications

Department of Radio Electronic Means

Area of expertise: RF spectrum management

197022

5 F, Professor Popov St.

Saint Petersburg

huunghiht@gmail.comhttps://orcid.org/0000-0003-4144-222XPodstrigaevA. S.PodstrigaevA. S.

Aleksey S. Podstrigaev, Cand. Sci. (2016), Associate Professor. The author of more than 120 scientific publications

Department of Radio Electronic Means

Area of expertise: design of complex radio systems; microwave devices; digital signal processing; wideband receivers

197022

5 F, Professor Popov St.

Saint Petersburg

Aleksey S. Podstrigaev, Cand. Sci. (2016), Associate Professor. The author of more than 120 scientific publications

Department of Radio Electronic Means

Area of expertise: design of complex radio systems; microwave devices; digital signal processing; wideband receivers

197022

5 F, Professor Popov St.

Saint Petersburg

ap0d@ya.ruhttps://orcid.org/0000-0001-6626-893XNhanNguyen TrongNhanNguyen Trong

Nguyen Trong Nhan, Cand. Sci. (2023), scientific collaborator. The author of more than 25 scientific publications

Area of expertise: radio engineering and telecommunications

Bac Tu Liem

236, Hoang Quoc Viet St.

Hanoi

Nguyen Trong Nhan, Cand. Sci. (2023), scientific collaborator. The author of more than 25 scientific publications

Area of expertise: radio engineering and telecommunications

Bac Tu Liem

236, Hoang Quoc Viet St.

Hanoi

10th20th30th@gmail.comhttps://orcid.org/0009-0008-4157-3370IkonenkoD. A.IkonenkoD. A.

Danil A. Ikonenko, Master’s Student

Department of Computer Science and Engineering

Area of expertise: radio engineering and telecommunications

197022

5 F, Professor Popov St.

Saint Petersburg

Danil A. Ikonenko, Master’s Student

Department of Computer Science and Engineering

Area of expertise: radio engineering and telecommunications

197022

5 F, Professor Popov St.

Saint Petersburg

dan-ikonenko@mail.ruSaint Petersburg Electrotechnical UniversityРоссияSaint Petersburg Electrotechnical UniversityRussian FederationLe Quy Don Technical UniversityВьетнамLe Quy Don Technical UniversityViet Nam2023281120232654049Copyright © Nghi T.H., Podstrigaev A.S., Nhan N.T., Ikonenko D.A., 20232023Nghi T.H., Podstrigaev A.S., Nhan N.T., Ikonenko D.A.Nghi T.H., Podstrigaev A.S., Nhan N.T., Ikonenko D.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://re.eltech.ru/jour/article/view/798   Introduction

   Introduction. The signal recognition task for the purposes of RF spectrum management can be solved using a signal recognition algorithm with detection at two intermediate frequencies. This algorithm is based on time–frequency analysis using fast Fourier transform (FFT) and signal envelope processing. Due to the relative simplicity of transformations, this algorithm is implemented on commercially available field programmable gate arrays and allows processing received signals in near real-time. However, the justification of the algorithm parameters providing effective signal recognition by the criterion of minimizing the signal-to-noise ratio (SNR) has not performed so far.

   Aim

   Aim. Justification of parameters of the developed signal recognition algorithm, providing the minimum required SNR at the algorithm input.

   Materials and methods

   Materials and methods. The efficiency of the developed algorithm was estimated by computer simulation in the MATLAB environment.

   Results

   Results. The influence of the parameters of functional blocks and received signals on the efficiency of the developed algorithm was investigated. For chirp, simple pulse, binary, and quadrature phase shift keying signals, the following parameters are recommended: a pulse duration of 5…20 μs; a chirp rate of 0.8…24 MHz/μs; a code duration of 0.5…1 μs. For these signal parameters, the parameters of the algorithm ensuring its efficiency according to the given criterion are as follows: the number of FFT points equals 1024; the Hamming weight window; bandwidths of band-pass filters are 4 MHz; signal envelope amplitude averaging coefficient equals 0.15…0.25.

   Conclusion

   Conclusion. The algorithm with the scientifically valid parameters can be used for recognition of signals at the input minimum SNR for the given types and parameters of signals.

   Introduction

   Introduction. The signal recognition task for the purposes of RF spectrum management can be solved using a signal recognition algorithm with detection at two intermediate frequencies. This algorithm is based on time–frequency analysis using fast Fourier transform (FFT) and signal envelope processing. Due to the relative simplicity of transformations, this algorithm is implemented on commercially available field programmable gate arrays and allows processing received signals in near real-time. However, the justification of the algorithm parameters providing effective signal recognition by the criterion of minimizing the signal-to-noise ratio (SNR) has not performed so far.

   Aim

   Aim. Justification of parameters of the developed signal recognition algorithm, providing the minimum required SNR at the algorithm input.

   Materials and methods

   Materials and methods. The efficiency of the developed algorithm was estimated by computer simulation in the MATLAB environment.

   Results

   Results. The influence of the parameters of functional blocks and received signals on the efficiency of the developed algorithm was investigated. For chirp, simple pulse, binary, and quadrature phase shift keying signals, the following parameters are recommended: a pulse duration of 5…20 μs; a chirp rate of 0.8…24 MHz/μs; a code duration of 0.5…1 μs. For these signal parameters, the parameters of the algorithm ensuring its efficiency according to the given criterion are as follows: the number of FFT points equals 1024; the Hamming weight window; bandwidths of band-pass filters are 4 MHz; signal envelope amplitude averaging coefficient equals 0.15…0.25.

   Conclusion

   Conclusion. The algorithm with the scientifically valid parameters can be used for recognition of signals at the input minimum SNR for the given types and parameters of signals.

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The authors declare that there are no conflicts of interest present.