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Digital technologies for signal radio vision and radio monitoring

https://doi.org/10.32362/2500-316X-2024-12-4-59-69

EDN: PYJISU

Abstract

Objectives. Radiophysical processes involving the electrodynamic formation of signal radio images diffusely scattered by the signature of small-sized objects or induced by the near field of radio devices are relevant for identifying radiogenomic (cumulant) features of objects in the microwave range in the development of neuroimaging ultra-short pulse (USP) signal radio vision systems, telemonitoring, and near-radio detection. The paper sets out to develop methods and algorithms for vector analysis of radio wave deformation of nonstationary fields forming a signal radio image based on radiophysical and topological characteristics of small-sized objects; to develop software and hardware for registration and neural network recognition of signal radio images, including methods for the synthesis and extraction of signal radiogenomes using digital twins of objects obtained through vector electrodynamic modeling; and to analyze signal radio images induced by elements of printed topology of electronic devices.
Methods. The study is based on statistical radiophysics methods, time-frequency approaches for wavelet transformation of USP radio images, numerical electrodynamic methods for creating digital twins of small-sized objects, as well as neural network authentication algorithms based on the cumulant theory of pole-genetic and resonant physically unclonable functions used in identifying signal radio images.
Results. The results of fundamental research on electrodynamic effects of vector-wave deformation of nonstationary fields of sub-nanosecond configuration are presented as a means of identifying and authenticating signal radio images. Neural network techniques for cumulant formation of radio genomes of signal radio images are proposed on the basis of pole-genetic and resonant functions.
Conclusions. A radiogenome, representing the unique authenticator of a radio image, is shown to be formed on the basis of physically unclonable functions determined by the structure and set of radiophysical parameters of the image. Cumulant features of signal radio images identified on the basis of pole-genetic and physically unclonable resonant functions of small-sized objects are revealed.

About the Authors

M. S. Kostin
MIREA – Russian Technological University
Russian Federation

Mihail S. Kostin, Dr. Sci. (Eng.), Associate Professor, Head of the Department of Radio Wave Processes and Technologies, Deputy Director, Institute of Radio Electronics and Informatics

78, Vernadskogo pr., Moscow, 119454

Scopus Author ID 57208434671



K. A. Boikov
MIREA – Russian Technological University
Russian Federation

Konstantin A. Boikov, Dr. Sci. (Eng.), Associate Professor, Department of Radio Wave Processes and Technologies, Institute of Radio Electronics and Informatics

78, Vernadskogo pr., Moscow, 119454

Scopus Author ID 57208926258



References

1. Kostin M.S., Boikov K.A. Radiovolnovye tekhnologii subnanosekundnogo razresheniya: monografiya (Radio Wave Technologies of Subnanosecond Resolution: monograph). Moscow: RTU MIREA; 2021. 142 p. (in Russ.). ISBN 978-5-7339- 1565-4

2. Kostin M.S., Boikov K.A. Signal’no-arkhitekturnyi reinzhiniring i radiosensornoe raspoznavanie elektronnykh sredstv (Signal- Architectural Reengineering and Radiosensor Recognition of Electronic Devices: textbook). Moscow; Vologda: Infra-Inzheneriya; 2024. 152 p. (in Russ.). ISBN 978-5-9729-1832-4

3. Shadinov S.S. Spatial ultra-wideband visualization of probed near-field surveillance objects. Zhurnal Radioelektroniki = J. Radio Electronics. 2020;7 (in Russ.). https://doi.org/10.30898/1684-1719.2020.7.8. Available from URL: http://jre.cplire.ru/jre/jul20/8/text.pdf

4. Nerukh A., Benson T. Non-stationary Electromagnetics. USA: Jenny Stanford Publishing; 2012. 616 p. https://doi.org/10.1201/b13058

5. Allen B., Dohler M., Okon E.E., et al. Ultra-Wideband Antennas and Propagation for Communications, Radar and Imaging. USA: John Wiley & Sons; 2007. 475 p.

6. Mahafza B.R. Radar Signal Analysis and Processing Using Matlab. USA: CRC Press; 2016. 504 p.

7. Carrer L., Yarovoy A.G. Concealed weapon detection using UWB 3-D radar imaging and automatic target recognition. In: The 8th European Conference on Antennas and Propagation (EuCAP). 2014. Р. 2786–2790. https://doi.org/10.1109/EuCAP.2014.6902403

8. Günther L. Electromagnetic Field Theory for Engineers and Physicists. Berlin, Heidelberg: Springer; 2010. 659 p.

9. Oppermann I., Hämäläinen M., Iinatti J. UWB: Theory and Applications. John Wiley & Sons; 2004. 248 p.

10. Taylor J.D. (Ed.). Advanced Ultrawideband Radar. Signals, Targets, and Advanced Ultrawideband Radar Systems. Boca Raton, USA: CRC Press; 2016. 494 p.

11. Wang X., Dinh A., Teng D. Radar Sensing Using Ultra Wideband – Design and Implementation. In: Matin M.A. (Ed.). Ultra Wideband – Current Status and Future Trends. 2013;11:41–63. https://dx.doi.org/10.5772/48587

12. Shadinov S.S., Kostin M.S., Konyashkin G.V., et al. Vector S-Parametric Analysis of Signal Phase Dynamic Radio Images. Dokl. Phys. 2023;68(9):311–318. https://doi.org/10.1134/S1028335823090057 [Original Russian Text: Shadinov S.S., Kostin M.S., Konyashkin G.V., Korchagin A.S., Romanovskii M.Yu., Gusein-zade N.G. Vector S-parametric analysis of signal phase dynamic radio images. Doklady Rossiiskoi akademii nauk. Fizika, tekhnicheskie nauki. 2023;512(1):78–86 (in Russ.). https://doi.org/10.31857/S2686740023050115 ]

13. Boikov K.A. Determination of parameters of electronic devices by the method of passive radio-sensor technical diagnostics. Izvestiya vysshikh uchebnykh zavedenii Rossii. Radioelektronika = Journal of the Russian Universities. Radioelectronics. 2021;24(6):63–70 (in Russ.). https://doi.org/10.32603/1993-8985-2021-24-6-63-70

14. Lebedev E.F., Ostashev V.E., UlyanovA.V. Means for generating ultra-wideband radio frequency emissions with semiconductor field generators. Vestnik Kontserna VKO Almaz-Antei = Bulletin of Concern VKO Almaz-Antey. 2018;1(24):35–42 (in Russ.).

15. Boikov K.A., Shamin A.E. Software Analysis of the Signal Radio Profile during Passive Radio-Sensor Technical Diagnostics. J. Commun. Technol. Electron. 2022;67(11):1337–1344. https://doi.org/10.1134/S1064226922110018

16. Astakhov N.V., Bashkirov A.V., Zhurilova O.E., Makarov O.Yu. Time-frequency analysis of non-stationary signals by wavelet transform and windowed Fourier transform. Radiotekhnika = Radioengineering. 2019;83(6-8):109–112 (in Russ.).

17. Herder C., Ren L., van Dijk M., Yu M.-D., Devadas S. Trapdoor Computational Fuzzy Extractors and Cryptographically- Secure Physical Unclonable Functions. IEEE Transactions on Dependable and Secure Computing. 2017;14(1):65–82. https://doi.org/10.1109/TDSC.2016.2536609

18. Lukyanchikov A.V., Lyzlov A.V. Radio broadcast monitoring system using SDR technology. SVCh-tekhnika i telekommunikatsionnye tekhnologii = Microwave and Telecommunication Technology. 2021;3:69–70 (in Russ.). Available from URL: https://elibrary.ru/dxiqdb

19. Huang R., Cui H. Consistency of chi-squared test with varying number of classes. J. Syst. Sci. Complex. 2015;28(2):439–450. https://doi.org/10.1007/s11424-015-3051-2

20. Liu Y., Mu Y., Chen K., et al. Daily Activity Feature Selection in Smart Homes Based on Pearson Correlation Coefficient. Neural Process. Lett. 2020;51(2):1771–1787. https://doi.org/10.1007/s11063-019-10185-8


Supplementary files

1. Signal radio profile three-dimensional spectrum
Subject
Type Исследовательские инструменты
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Indexing metadata ▾
  • The results of fundamental research on electrodynamic effects of vector-wave deformation of nonstationary fields of sub-nanosecond configuration are presented as a means of identifying and authenticating signal radio images.
  • Neural network techniques for cumulant formation of radio genomes of signal radio images are proposed on the basis of pole-genetic and resonant functions.
  • A radiogenome, representing the unique authenticator of a radio image, is shown to be formed on the basis of physically unclonable functions determined by the structure and set of radiophysical parameters of the image.
  • Cumulant features of signal radio images identified on the basis of pole-genetic and physically unclonable resonant functions of small-sized objects are revealed.

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Kostin M.S., Boikov K.A. Digital technologies for signal radio vision and radio monitoring. Russian Technological Journal. 2024;12(4):59–69. https://doi.org/10.32362/2500-316X-2024-12-4-59-69. EDN: PYJISU

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ISSN 2782-3210 (Print)
ISSN 2500-316X (Online)