V.D. Usoltseva1

1 JSC “CNIRTI named after academician A.I. Berg” (Moscow, Russia)

1 lera.usoltseva.2014@mail.ru

The task of determining the parameters of objects based on their infrared characteristics is one of the key challenges in the field of electronic warfare. However, traditional methods for solving this problem require a significant computational resource, which limits their application in real-time conditions. Therefore, the development of a universal and efficient method based on the use of neural networks appears to be relevant and in demand.

Despite the detailed description of the signal recognition problem in the radio frequency range using neural networks, the issue of a similar problem in the infrared range remains unresolved. In this regard, addressing the task of object recognition based on its signal characteristics in the infrared wavelength range using the neural network described in this work is both relevant and in demand.

Experimental studies have shown that the proposed method ensures high accuracy in object recognition. The results confirmed that the radial basis neural network can effectively tackle the task of classifying objects in the infrared range, making this approach promising for practical applications.

The use of the proposed method significantly reduces the time and computational costs associated with object recognition tasks. Due to its adaptability to various input data, the method can be successfully applied in optoelectronic surveillance systems, enhancing their efficiency and lowering operational costs.

Usoltseva V.D. The solution to the object recognition problem based on its trajectory and signal characteristics in the infrared wavelength range using of radial-basis neutron network. Radiotekhnika. 2025. V. 89. № 5. P. 37−44. DOI: https://doi.org/10.18127/j00338486-202505-04 (In Russian)

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