Method for transforming symbolic radar marks of low-noticeable moving objects based on the Talbot effect
DOI:
https://doi.org/10.30837/rt.2021.2.205.14Keywords:
symbolic image, non-stationary radar marker, Tabolt effect, detection, recognition, intellectual analysisAbstract
In this paper a method to transform radar images of moving aerial objects with scintillating inter-period fluctuations, sometimes resulting to complete signal fading, using the Talbot effect is considered. These transformations are reduced to the establishment of a certain correspondence of the asymptotic equality of perception of visual images, arbitrarily changing in time and space, in the statement about the conditions of simple equality of perception of images of radar marks that have different frequencies of fluctuations. It is shown how this approach can be used to analyze radar data by transforming and smoothing scintillating signal fluctuations, invisible in the presence of interference, into visible symbolic images. First, to detect and recognize the aerial objects from the analysis of relations and functional (semantic) dependencies between attributes, second, to make a decision based on semantic components of symbolic radar images. The possibility of using such transformation to generate pulse-frequency code of fluctuations of the symbolic radar angel-echo images as an important characteristic for their recognition has been experimentally verified. Algorithms for generating symbolic images in asynchronous and synchronous pulse-frequency code are formulated. The symbolic image represented by such a code is considered as an additional feature for recognizing and filtering out natural interferences such as angel-echoes.
References
Сколник М.И. Справочник по радиолокации : в 2 т. ; пер. с англ. под ред. B.C. Вербы. Москва : Тех-носфера, 2014. 672 с.
Li Jian. Radar Signal Processing and Its Applications / Jian Li, R. Hummel, P. Stoica, E. G. Zelnio. Springer, 2013. 279 p.
Talbot H.F. Experiments on light. Phil. Mag., (third series), № 5. 1834. р. 321.
Теплов Б.М., Яковлева С.П. О законах пространственного и временного смешения цветов // Зрительные ощущения и восприятия. Т.2. Москва : Соцэкгиз, 1935.
Ильин В.Д., Соколов И.А. Символьная модель системы знаний информатики в человеко-автоматной среде // Информатика и ее применения. 2007. Т. 1 №1. С. 66-78.
Solonska S., Zhyrnov V. Adaptive semantic analysis of radar data using fuzzy transform (Book Chapter). Springer, 2020, Lecture Notes on Data Engineering and Communications Technologies. Vol 48. P. 157-179.
Zhuravlev Yu. I. Analysis of a training sample and classification in one recognition model / Yu. I. Zhuravlev, L. A. Aslanyan, V. V. Ryazanov // Pattern Recognition and Image Analysis: Pleiades Publishing, 2014. Vol. 24, Issue 3. pp 347–352. https://doi.org/10.1134/S1054661814030183.
Solonskaya S.V., Zhirnov V.V. Intelligent analysis of radar data based on fuzzy transforms // Telecommunications and Radio Engineering (English translation of Elektrosvyaz and Radiotekhnika). 2018. 77 (15), pp. 1321-1329.|Scopus|0.69|
Solonskaya S.V., Zhirnov V.V. Signal processing in the intelligence systems of detecting low-observable and low-doppler aerial targets // Telecommunications and Radio Engineering (English translation of Elektrosvyaz and Radio-tekhnika). 2018. Vol. 77, Issue 20. P. 1827-1835.
Zhyrnov V., Solonska S. PROCESS KNOWLEDGE BOUT OBSERVED OBJECTS IN INTELLECTUAL MONITORING SYSTEMS // Telecommunications and Radio Engineering. 2020. Vol. 79, Issue 18, P. 1599-1607. |Scopus|0.69|. DOI: 10.1615/TelecomRadEng.v79.i18.20.
Zhyrnov V., Solonska S. INTELLIGENT SYSTEM FOR DETECTION OF LOW-VISIBLE AIR OBJECTS IN SURVEILLANCE RADARS // Telecommunications and Radio Engineering. 2020. Vol. 79, Issue 17, P. 1513-1519. |Scopus|0.69|. DOI: 10.1615/TelecomRadEng.v79.i17.20.
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