International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges

Vitaliy Garmash
Department of Radio Electronic Systems, Baltic State Technical University, Russia.

Yuriy Petrov
Department of Radio Electronic Systems, Baltic State Technical University, Russia.

Andrey Andreev
Department of Technosphere Safety, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195220, Russia.

Anatoly Zaitsev
Department of Technosphere Safety, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, 195220, Russia.


Received on December 05, 2018
Accepted on September 13, 2019


This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.

Keywords- Radar signal, Radar cross-section, Digital image processing, Nonlinear processing, Adaptive contrasting.


Garmash, V., Petrov, Y., Andreev, A., & Zaitsev, A. (2019). Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges. International Journal of Mathematical, Engineering and Management Sciences, 4(6), 1448-1458.

Conflict of Interest

The authors confirm that there is no conflict of interest to declare for this publication.


The work was carried out in accordance with the decree of the Government of the Russian Federation from 09.04.2010 № 218 (PROJECT 218) in the framework of R&D, executing with the financial support of the Ministry of education and science of the Russian Federation (agreement № 074-11-2018-025 from 13.07.2018). Work is performed in lead R & D performer organization: Federal State Budgetary Educational Institution of Higher Professional Education BSTU "VOENMEH" named after D.F. Ustinov.

The research carried out with the financial support of the grant from the Program Competitiveness Enhancement of Peter the Great St. Petersburg Polytechnic University.


Barton, D.K. (2013). Radar equations for modern radar. 1st Edition. Artech House Radar.

Bataev, A.V. (2019) Efficiency estimation model of 3D technology in the construction industry. In 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019, art. no. 8657181, pp. 1376-1381. doi: 10.1109/EIConRus.2019.8657181.

Davydov, V.V., Dudkin, V.I., & Myazin, N.S. (2016). Nutation line shape for the nonstationary regime of magnetic resonance flowmeter–relaxometer. Journal of Communications Technology and Electronics, 61(10), 1159-1165. doi:10.1134/S1064226916100077.

EUROCAE ED-179 (2011). Minimum aviation system performance standard (MASPS) for enhanced vision systems, synthetic vision systems, combine vision systems and enhanced flight vision systems. The European Organisation for Civil Aviation Equipment.

Galeeva, M.A., Baranov, M.A., Pavlov, V.A., Velichko, E.N., Zavjalov, S.V., Govorov, I.E., Pervunina, T.M., &. Komlichenko, E.V. (2019) On specific features of the endoscopic image processing. Journal of Physics: Conference Series, 1236 (1), art. no. 012036, doi: 10.1088/1742-6596/1236/1/012036.

Ivanov, S.I., Kyrnyshev, A.M., & Lavrov, A.P. (2015). Measuring radar cross-section of complex-shaped objects using the doppler shift. Paper presented at the 2015 International Siberian Conference on Control and Communications, SIBCON 2015 – Proceedings (pp. 1-4). IEEE. Omsk, Russia. doi:10.1109/SIBCON.2015.7147075.

Ivanov, S.I., Lavrov, A.P., Saenko, I.I., Bessoltsev, S.A., Dostovalov, A.V., & Wolf, A.A. (2018). Microwave photonic beamforming system with broadband chirped fiber bragg grating. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, 10774. doi:10.1117/12.2318086.

Jobson, D.J., Rahman Z., & Woodell, G.A. (1997). A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Transactions Image Process 6(7), 965–976.

Johnson, C. (2007). The practical zone system: for film and digital photography. 4th Edition. Boston, Focal Press.

Kaasik, V.P. & Rogov, S.A. (2016). Comparison of the operation of an acousto-optic spectrum analyzer and an acousto-optic pseudo-wigner processor by analyzing the time-frequency distributions of frequency-modulated signals. Journal of Optical Technology (A Translation of Opticheskii Zhurnal), 83(5), 290-294. doi:10.1364/JOT.83.000290.

Klochkov, Y., Gazizulina, A., Golovin, N., Glushkova, A., & Zh, S. (2018). Information model-based forecasting of technological process state. Paper presented at the 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, (ICTUS 2017) (pp. 709-712).IEEE. ADET, Amity University Dubai, UAE. doi:10.1109/ICTUS.2017.8286099.

Kondratenkov, G.S., & Frolov, A.Y. (2005). Radio broadcasting. Radar systems for remote sensing of the Earth. Textbook for high schools. Moscow, Radiotekhnika.

Korobeynikov, A.G., Grishentsev, A.Yu., Velichko, E.N., Korikov, C.C., Aleksanin, S.A., Fedosovskii, M.E., & Bondarenko, I.B. (2016). Calculation of regularization parameter in the problem of blur removal in digital image. Optical Memory and Neural Networks (Information Optics), 25(3), 184-191. doi:10.3103/S1060992X16030036.

Land, E.H., & McCann, J.J. (1971). Lightness and retinex theory. Journal of the Optical Society of America. 61(1), 1–11.

Logunov, S.E., Davydov, V.V., Vysoczky, M.G., & Titova, O.A. (2018). Peculiarities of registration of magnetic field variations by a quantum sensor based on a ferrofluid cell. Journal of Physics: Conference Series, 1135(1), art. no. 012069. doi: 10.1088/1742-6596/1135/1/012069.

Mather, P., & Tso, B. (2009). Classification methods for remotely sensed data. second edition. CRC Press, Taylor and Francis Group, Boca Raton, USA.

Matveev, S.A., Bizov, A.N., Bistrov, S.Yu., Garmash, V.N., Isenko, S.I., Korobochkin, D.M., Petrov, Yu.V., Rudika, S.A., Strahov, S.Yu., & Sircev, A.N. (2018). Helicopter system that provide information support for safety of flights and conduct search and rescue operations. Bulletin of the Kyrgyz-Russian Slavic University, 18(9), 60-64.

Meena, D., & Prakasam, L.G.M. (2008). FPGA based real time solution for sensitivity time control. In 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008) (pp. 244-248). IEEE. Hong Kong, China.

Munson, J., & Cox, F. (2013). Video circuit collection. In Analog Circuit Design. Vol. 2. Immersion in the Black Art of Analog Design Chapter 34 (pp. 769-800). Editors: Dobkin, B. & Williams, J. Elsevier.

Pasmurov, A.Y., & Zinoviev, J.S. (2005). Radar imaging and holography. IET radar, sonar and navigation series 19. London, United Kingdom.

Privalov, V.E., & Shemanin, V.G. (2017). Estimation of the error of lidar measurements of atmospheric radionuclide concentrations. Measurement Techniques, 60(9), 962-967. doi:10.1007/s11018-017-1301-5.

Privalov, V.E., & Shemanin, V.G. (2018). Monitoring hydrogen sulfide molecules in the atmospheric boundary layer by differential absorption and scattering lidar from space. Journal of Optical Technology (A Translation of Opticheskii Zhurnal), 85(4), 229-232. doi:10.1364/JOT.85.000229.

Shang, W., Xu, Y., Qi, J., Xue, W., & Makarov, S.B. (2017). Optimal waveform of the partial-respond signal based on minimum out-of-band radiation criterion. Applied Sciences (Switzerland), 7(10), 1-12 doi:10.3390/app7101086.

Shelton, K.J., Kramer, L.J., Ellis, K., & Rehfeld, S.A. (2012). Synthetic and enhanced vision systems (sevs) for nextgen simulation and flight test performance evaluation. In 2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC) (pp. 2D5-1). IEEE. Williamsburg, VA, USA.

Skolnic, M.I. (1990). Radar handbook. 2nd Edition. McGraw-Hill Professional.

Tarasenko, M.Yu., Davydov, V.V., Lenets, V.A., Akulich, N.V., & Yalunina, T.R. (2017) Features of use direct and external modulation in fiber optical simulators of a false target for testing radar station. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10531 LNCS, pp. 227-232 DOI: 10.1007/978-3-319-67380-6_21.

van Vliet, L.J., Young, I.T., & Verbeek, P.W. (1998). Recursive Gaussian derivative filters. In proceedings of Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170). IEEE. Brisbane, Queensland, Australia.

Vygolov, O.V. (2013). Enhanced and synthetic vision systems development based on integrated modular avionics for civil aviation. IEEE/AIAA 32st Digital Avionics Systems Conference (DASC’2013), 2B5.1-2B5.13. IEEE. East Syracuse, NY, USA.

Zheltov, S., & Vygolov, O.V. (2015). Enhanced, synthetic and combined vision technologies for civil aviation. In Computer Vision in Control Systems-2 (pp. 201-230). Springer, Cham.

Ziniakov, V.Y., Gorodetskiy, A.E., & Tarasova, I.L. (2016). Control of vitality and reliability analysis. In Smart Electromechanical Systems (pp. 193-204). Springer, Cham. doi:10.1007/978-3-319-27547-5_18.

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