V.B. Suchkov1, A.Y. Perov2, N.A. Zelnitskiy3

1-3 Bauman Moscow State Technical University (Moscow, Russia)

1 vbs-2014@bmstu.ru; 2 perovau@bmstu.ru; 3 zelnitsky@student.bmstu.ru

Statement of the problem: To improve the efficiency of radar ta rget recognition, a representative and large-scale sample of ra dar images of target objects is required. At the same time, obtaining highly detailed radar images based on polygonal models of obje cts with a large number of facets in an inverse aperture synthesis radar is combined with low computational complexity and signifi cant time expenditure. So the problem of optimizing the generation o f radar images for wide-angle fi elds of view based on multipoin t target models in which backscatter patterns are pre-calculated usi ng asymptotic methods has become relevant. This necessitates th e development of algorithms for a comprehensive quantitative assessment of the accuracy and efficiency of high-contrast radar im age synthesis methods. Purpose. To develop an algorithm for generating radar images of geometrically complex objects in radar systems with inverse ap erture synthesis based on their polygonal and multipoint models.

Results. Polygonal and multipoint models of the Bayraktar TB2 a nd MQ-9 Reaper unmanned aerial v ehicles (UAVs) have been developed to generate their radar images using X-band inverse synthe tic aperture radar. A method for generating high-contrast radar images using simulation modeling of inverse synthetic aperture radar systems is proposed. A comparative analysis of radar image modeling techniques for two real-world targets—the Bayraktar TB2 a nd MQ-9 Reaper UAVs—was conducted using two fundamentally different approaches to object representation: a detailed polygona l model and a simplified multipoint (point-scatter) model. An a lgorithmic complex for processing reflected signals and constructi ng radar images from specified angles based on polygonal and mu ltipoint models was implemented in the MATLAB environment. The r esults of the work substantiate the possibility of using the pr oposed algorithm, based on a multi-point representation of the target, to form representative training samples with a significant reduction in computational costs.

Practical significance. The developed algorithm for synthesizin g radio images based on a multipoint target representation enab les the formation of a representative training sample of target radio i mages, significantly reducing computational costs compared to d etailed polygonal models. The obtained results expand on existing metho ds and can be used to create effective tools for generating hig hly detailed radar images for complex target recognition.

Suchkov V.B., Perov A.Yu., Zelnitskiy N.A. Analysis of radar images of unmanned aerial vehicles based on their polygonal and multipoint models using the back-projection method. Radiotekhni ka. 2026. V. 90. № 3. P. 168−180. DOI: https://doi.org/10.18127/j00338486-202603-15 (In Russian)

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27. Research methods and control algorithms in radio electronic systems 1
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