350 rub
Journal Electromagnetic Waves and Electronic Systems №3 for 2021 г.
Article in number:
Experimental assessment of the information content of long-range portraits of radar objects
Type of article: scientific article
DOI: https://doi.org/10.18127/j15604128-202103-02
UDC: 621.396
Authors:

V.E. Turov1, A.V. Zyuzin2, A.V. Timoshenko3 , V.P. Grutsya4

1,2,4 Yaroslavl Higher Military School of Air Defense (Yaroslavl, Russia),

3  Military University of Radioelectronics (Cherepovets, Russia)

victorturov@gmail.com, aleksey.zyuzin@mail.ru, u567ku78@gmail.com, grunyapal@yandex.ru

Abstract:

At present, the scientific and technical literature discusses in detail the issues of obtaining information about the geometric characteristics of airborne radar targets (RC), which can be used as recognition signs. However, these issues and the methods being developed are considered in relation to single-position radar stations (radars) using simple or complex signals.

Purpose of the work is determination of the informative value of the parameters of the long-range portraits of the RLS obtained by the method of statistical and physical modeling based on the processing of experimental data. A method is proposed for assessing the informativeness of long-range portraits of radar objects obtained as a result of processing reflected signals by various methods, including using weight processing based on a priori information about the structure of probing signals.

Based on the analysis of the experimental data, it was found that the weight processing of the long-range portraits of the RLS provides an increase in the contrast of the portraits (an increase in the steepness of the portrait peaks and the depth of the dips), which, in turn, leads to an increase in the information content of each element of the long-range portrait and the totality of the features of the long-range portrait as a whole when recognizing RLO.

The use of the technique allows us to assess the quality of the long-range portraits of the radar, obtained by various methods of processing radar signals and develop algorithms that increase the information content of radar systems with the recognition mode both for air and space radar and for objects against the background of the underlying surface during remote sensing.

Pages: 11-19
For citation

Turov V.E., Zyuzin A.V., Timoshenko A.V., Grutsya V.P. Experimental assessment of the information content of long-range portraits of radar objects. Electromagnetic waves and electronic systems. 2021. V. 26. № 3. P. 11−19. DOI: https://doi.org/10.18127/j15604128-202103-02 (in Russian)

References
  1. Akinshin O.N., Rumyantsev V.L., KHomyakov K.A. Otsenka informativnosti polyarizatsionnykh parametrov polyarizatsionnomodulirovannykh signalov. Elektronnye i informatsionnye sistemy. 2015. № 2(5). S. 35−43. (in Russian)
  2. Grutsya V.P. Model’ formirovaniya vesovykh koeffitsientov algoritma obnaruzheniya-razresheniya tseley na osnove apriornoy informatsii o parametrakh zondiruyushchikh signalov. Svid-vo o gosudarstvennoy registratsii programm dlya EVM. Zaregistrirovan v Reestre programm dlya EVM 06.02.2020 g. Svid-vo gosudarstvennoy registratsii № 2020610683. (in Russian)
  3. Vasin V.A., Vlasov I.B., Egorov Yu.M. i dr. Informatsionnye tekhnologii v radiotekhnicheskikh sistemakh. Pod red. I.B. Fedorova. M.: Izd-vo MGTU im. N.E. Baumana. 2011. 848 s. (in Russian)
  4. Pat. RF na poleznuyu model’ № 2793419. Kompleks polunaturnogo modelirovaniya pomekhovoy obstanovki. Zyuzin A.V., Turov V.E., Grutsya V.P., Alfer’ev A.V., Demochkin N.S.; zayavka 2019100153, zayavl. 25.04.2019, zaregistr. 09.01.2019. M.: FGU FIPS. 2019. (in Russian)
  5. Pat. RF na poleznuyu model’ № 2643360. Korrelyatsionno-fil’trovoy obnaruzhitel’. Zyuzin A.V., Turov V.E., Grutsya V.P., KHaybutov K.E., Poltoratskiy A.V.; zayavka 2017144244, zayavl. 18.12.2017, zaregistr. 17.05.2018. M.: FGU FIPS. 2018. (in Russian)
  6. Pat. RF na poleznuyu model’ № 2794512. Korrelyatsionno-fil’trovoy obnaruzhitel’ s vesovoy obrabotkoy. Zyuzin A.V., Turov V.E., Grutsya V.P.; zayavka 2019100936, zayavl. 25.01.2019, zaregistr. 28.03.2019. M.: FGU FIPS. 2019. (in Russian)
  7. Pat. RF na poleznuyu model’ № 139757. Korrelyatsionno-fil’trovoy obnaruzhitel’ pachki radioimpul’sov. Zyuzin A.V., Turov V.E., Grutsya V.P., Tikhonov D.L.; zayavka 2019139757, zayavl. 04.12.2019, zaregistr. 23.07.2019. M.: FGU FIPS. 2019. (in Russian)
  8. Kosenko G.G. Kriterii informativnosti pri razlichenii signalov. M.: Radio i svyaz’. 1982. 216 s. (in Russian)
  9. Kul’bak S. Teoriya informatsii i statistika. M.: Nauka. 1968. 302 s. (in Russian)
  10. Turov V.E., Il’inykh A.A., Zosiev V.V. S zabotoy o novykh tekhnologiyakh. Vestnik voennogo obrazovaniya. Iyul’-avgust 2018. № 4(13). S. 53−60. (in Russian)
  11. Fukunga K. Vvedenie v statisticheskuyu teoriyu raspoznavaniya obrazov. M.: Nauka. 1979. 368 s. (in Russian)
Date of receipt: 29.04.2021 г.
Approved after review: 27.05.2021 г.
Accepted for publication: 18.06.2021 г.