Ivan S. Ashurkov1, Sergey A. Zhitkov2, Ivan N. Zaharov3, Nikolay A. Leshko4, Anatoly V. Moroz5,  Igor V. Sakhno61,2,3,4

 Yaroslavl Higher Military Institute of Air Defense (Yaroslavl, Russia),  5,6

 Military Space Academy named after A.F. Mozhaisky (St. Petersburg, Russia)

To confirm the performance of the algorithms for detecting aerodynamic targets based on parametric transformations of a sample of true and false marks, physical modeling and a full-scale experiment are required. Full-scale tests of radar systems are associated with significant time and material costs due to the high cost of creating experimental samples of the complex, control and measuring equipment and the involvement of a significant number of personnel in the experiment. In a number of cases, for example, when studying the issues of secondary and tertiary processing, it is less costly to conduct an experiment on complexes of semi-natural modeling of location systems.

The aim of the work is to develop a simulation model of the detection process based on parametric transformations, which allows one to evaluate the detection efficiency under conditions of low signal-to-noise ratios during inter-point processing of radar information. A simulation model of the detection process was developed on the basis of the location acoustic complex aerodynamic targets. The testing of the algorithm for detecting straight-line trajectories of targets based on the Hough parametric transformation using this model has been carried out.

Practical significance – the ability to detect targets in conditions of low values of the signal-to-noise ratio. The presented model can be used in the hardware and software of modern radar stations.

Ashurkov I.S., Zhitkov S.A., Zaharov I.N., Leshko N.A., Moroz A.V., Sakhno I.V. Simulation model of the process of  detecting aerodynamic targets based on parametric transformations in a multi-position location system. Achievements of modern radioelectronics. 2020. V. 74. № 12. P. 32–44. DOI: 10.18127/j20700784-202012-03. [in Russian]

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