D.S. Korlyakov1

1 MIREA – Russian Technological University (Moscow, Russia)

1 Denis.Korlyakov.RIMO-01-21@yandex.ru

Formulation of the problem. The work is devoted to a promising method for processing signals and radar data. The wavelet transform allows you to perform high-quality signal filtering.

Target. Study of the properties of the discrete wavelet transform and its application to clean sounding radar signals from noise using modeling in Python.

Results. An analysis of radar data was carried out, code was written for modeling and filtering radar information.

Practical significance. The presented results create the basis for modernizing signal processing methods, namely radar information.

Korlyakov D.S. Functioning algorithms: transmission, reception and processing of signals using the wavelet transform to filter received radar signals. Radiotekhnika. 2024. V. 88. № 8. P. 140−145. DOI: https://doi.org/10.18127/j00338486-202408-13 (In Russian)

1. Denisova E.V., Hmelinin A.P. Issledovanie vlijanija fiziko-mehanicheskih svojstv geosredy na tochnost' geofizicheskih metodov pri lokacii podzemnyh ob’ektov. Gornyj informacionno-analiticheskij bjulleten': sb. nauch. statej IGD SO RAN. 2012. S. 107−109 (in Russian).
2. Berdyshev V.P., Garin E.N., Fomin A.N. i dr. Radiolokacionnye sistemy: Uchebnik. Pod obshh. red. V.P. Berdysheva. Krasnojarsk: SFU. 2011. 400 s. (in Russian).
3. Smolencev N.K. Osnovy teorii vejvletov. Vejvlety v MatLab. M.: DMK Press. 2005. 304 s. (in Russian).
4. Mitrofanov D.G. Struktura radiolokatora s inversnym sintezirovaniem apertury i mnogochastotnym zondirujushhim signalom. Radiotehnika. 2001. T. 65. № 5. S. 36−41 (in Russian).
5. Matveev B.V., Krjukov D.Ju., Kur'jan Ju.S., Levenkov K.O. Grimenenie diskretnogo vejvlet-preobrazovanija dlja fil'tracii zondirujushhih radiolokacionnyh signalov ot additivnyh pomeh. Vestnik VGTU. 2014. № 10. S. 43−46 (in Russian).
6. Jakovlev A.N. Vvedenie v vejvlet-preobrazovanija: Ucheb. posobie. Novosibirsk: Izd-vo NGTU. 2003. 104 s. (in Russian).
7. Semenchuk N.V., Dejceva A.G. Realizacija algoritma Mallata dlja vychislenija vejvletnyh ocenok spektral'nyh plotnostej. Stohasticheskoe i komp'juternoe modelirovanie sistem i processov: sb. nauch. statej. GrGU. 2011. 418 s. (in Russian).
8. Trush H.H. Asimptoticheskie metody statisticheskogo analiza vremennyh rjadov. Minsk: BGU. 1999. 218 s. (in Russian).
9. Semenchuk N.V. Ocenivanie velichiny smeshhenija i dispersii vejvletnoj ocenki spektral'noj plotnosti. Teorija verojatnostej, sluchajnye processy, matematicheskaja statistika i prilozhenija: sb. nauch. statej mezhdunar. nauch. konf. Minsk: BGU. 2008. S. 283−289 (in Russian).
10. Stoyanov D.D. Analysis of a modified nonparametric algorithm for detecting broadband radio signals. Proc. of the International Scientific and Practical Conf.: Technical Sciences: Theoretical and Applied Aspects (Tekhnicheskie nauki: teoreticheskie i prikladnye aspekty: materialy Mezhdunar. nauch.-prakt. konf.). Ufa. 2014. Р. 52−56.
11. Shevchenko M.E., Chemarov A.O. Detection and estimation of parameters of radio sources in a wide field of view. St. Petersburg. Publishing House of SPbGETU "LETI". 2010. 136 p.