RADIOELECTRONIC AND COMPUTER SYSTEMS

The production of parts and (or) finished products in electronics, mechanical engineering and other industries is inextricably linked with the control of the accuracy and cleanliness of the processed surfaces. Currently existing meters of parameters of statistically uneven surfaces, both contact and non-contact have some disadvantages, as well as limitations due to methods and design features of measurement. Speckle interferometric methods for measuring parameters of statistically uneven surfaces make it possible to get away from some disadvantages inherent in existing methods and measurements. The use of methods of statistical radio engineering, methods of optimization of statistical solutions and estimates of parameters of predictive distributions for optimal radio engineering system synthesis is promising for the analysis and processing optical-electronic coherent laser space-time signals (speckle images) form with the laser radiation scattered by statistically uneven surfaces. This work synthesizes the optimal algorithm and structure for analyzing the parameters of statistically-temporal surfaces based on spatio-temporal processing of optical speckle interference signals and images using modern methods of optimal synthesis of radio engineering and coherent optoelectronic systems. In this work, an algorithm for processing optical signals scattered by statistically uneven surfaces is synthesized and investigated for problems of optimal estimation of parameters and statistical characteristics of statistically uneven surfaces. A block diagram of the optical contactless device for evaluating the parameters of statistically uneven surfaces is proposed. The limiting errors of estimation parameters of statistically uneven surfaces and the optimal installation angles of the emitters and the optical receiver are investigated. Equations are obtained for estimating the root-mean-square height of the ridges and the correlation radius of small-scale statistically uneven surfaces in the approximation of small perturbations. The proposed method for evaluating the parameters of statistically uneven surfaces allows to increase the accuracy of measurements, to conduct a non-contact assessment of the parameters - even statistically uneven surfaces that have geometric surface irregularities or located in hard-to-reach places, for example, grooves, holes, as well as products of cylindrical, spherical and other shapes.

surface roughness; laser; speckle pattern; optimal algorithm; optical receiver; statistically uneven surfaces

Jian, Z. Jin, Z. Surface Roughness Measure Based on Average Texture Cycle. Second International Conference on Intelligent Human-Machine Systems and Cybernetics, 2010, pp. 298-302. DOI: 10.1109/IHMSC.2010.174.

Somthong, T. and Yang, Q. Surface roughness measurement using photometric stereo method with coordinate measuring machine. IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016, pp. 1-6. DOI: 10.1109/I2MTC.2016.7520329.

Cao, W., Cai, Z. and Ye, B. Measuring Multiresolution Surface Roughness Using V-System. IEEE Transactions on Geoscience and Remote Sensing, 2018, vol. 56, no. 3, pp. 1497-1506. DOI: 10.1109/TGRS.2017.2764519.

Li, Z. and Liu, J. The In-process and Real-Time Roughness Measuring System Design for Free-Form Surface. International Conference on Computational and Information Sciences, 2010, pp. 824-826. DOI: 10.1109/ICCIS.2010.205.

Xu, X. and Hu, H. Development of Non-contact Surface Roughness Measurement in Last Decades. International Conference on Measuring Technology and Mechatronics Automation, 2009, pp. 210-213. DOI: 10.1109/ICMTMA.2009.584.

Gu, X., Tsang, L. and Braunisch, H. Estimation of Roughness-Induced Power Absorption From Measured Surface Profile Data. IEEE Microwave and Wireless Components Letters, 2007, vol. 17, no. 7, pp. 486-488. DOI: 10.1109/LMWC.2006.899296.

Tabenkin, A. N., Tarasov, S. B., Stepanov, S. N. Sherokhovatost', volnistost', profil' [Roughness, waviness, profile]. St. Petersburg, Izdatel'stvo Politekhnicheskogo universiteta Publ., 2007. 136 p.

Qian, X.-F., Malhotra, T., Vamivakas, A. N., Eberly, J. H., Coherence constraints and the last hidden optical coherence. Phys. Rev. Lett., 2016, vol. 117, article no. 153901.

Dulevich, V. E. Teoreticheskie osnovy statisticheskoi radiotekhniki. Kn. 1 [Theoretical Foundations of Radiolocation]. Moscow, Sov. Radio Publ., 1964. 732 p.

Stepanenko, V. D., et al. Radiolokatsiya v metrologii [Radiolocation in metrology]. Leningrad, Gidrometeoizdat, 1973. 343 p.

Levin, B. R. Teoreticheskie osnovy statisticheskoi radiotekhniki. Kn. 1 [Theoretical Foundations of Statistical Radio Engineering, Book 1]. Moscow, Sov. Radio Publ., 1969. 752 p.

Bakut, P.A.; et al. Voprosy statisticheskoi teorii radiolokatsii. Tom 1 [Questions of the statistical theory of radar. Volume 1] Moscow, Sov. Radio Publ., 1963. 424 p.

Kotel’nikov, V. A. Sobranie trudov. V 3-kh tomakh. Tom 1. Radiofizika, informatika, telekommunikatsii [Collection of works. In 3 volumes. Volume 1. Radiophysics, Informatics, Telecommunications]. Moscow, Fizmatlit Publ., 2008. 517 p.

Dashian, S., Nahapetian, B. S. On the relationship of energy and probability in models of classical statistical physics, 2019, HAL Id: hal-01893829v4.

Bender, N., Yilmaz, H., Bromberg, Y. & Cao, H. Customizing Speckle Intensity Statistics. Optica, 2017, vol. 5, pp. 595–600.

Ishimaru, A. Wave propagation and scattering in random media. New York, Academic Press Publ., 1978. 572 p.

Solomentsev, O., Shcherbyna, O., Ostroumov, I., Sushchenko, O., Averyanova, Y. et al., Heteroskedasticity Analysis During Operational Data Processing of Radio Electronic Systems. Data Science and Security. Lecture Notes in Networks and Systems, 2021, vol. 290, Singapore, Springer Publ., 2021, pp. 168-175. DOI: 10.1007/978-981-16-4486-3_18.

Oliv'e, V. M. Mertsayushchie pyatna i statisticheskaya difraktsiya [Flickering spots and statistical diffraction]. TIIER, Moscow, 1963, no. 1, pp. 263–264.

Averyanova, Y., Sushchenko, O., Ostroumov, I., Kuzmenko, N., Zaliskyi, M., Solomentsev, O. UAS Cyber Security Hazards Analysis and Approach to Qualitative Assessment. Data Science and Security. Lecture Notes in Networks and Systems, 2021, vol. 290. Singapore, Springer Publ., 2021, pp. 258-265. DOI: 10.1007/978-981-16-4486-3_28.

Ostroumov, I., Kuzmenko, N., Sushchenko, O., Pavlikov, V., Zhyla, S., Solomentsev, O., et al. Modelling and simulation of DME Navigation global Service volume. Advances in Space Research, 2021, vol. 68, iss. 8, pp. 3495-3507. DOI: 10.1016/j.asr.2021.06.027.

Ieremeiev, O., Lukin, V., Okarma, K. Kombinovana metryka vizual'noyi yakosti zobrazhen' dystantsiynoho zonduvannya na osnovi neyronnoyi merezhi [Combined visual quality metric of remote sensing images based on neural network]. Radioelektronni i komp'uterni sistemi – Radioelectronic and computer systems, 2020, no. 4(96), pp. 4-15. DOI: 10.32620/reks.2020.4.01.

Abramov, S. K., Abramova, V. V., Abramov, K. D., Lukin, V. V., Bondar, V. V., Kaluzhinov, I. V. Metodika opredelenija polja obnaruzhenija bespilotnyh letatel'nyh apparatov nazemnym nabljudatelem [Technique of detection field estimating for unmanned aerial vehicles by a ground observer]. Radioelektronni i komp'uterni sistemi – Radioelectronic and computer systems, 2020, no. 3(95), pp. 36-42. DOI: 10.32620/reks.2020.3.04.