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Optical Methods for Detecting and Tracking Moving Objects in the Atmosphere

  • CHEMICAL PHYSICS OF ATMOSPHERIC PHENOMENA
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Abstract

Progress in the development of infrared (IR) laser diodes, photodetector elements of matrices in the visible and IR ranges, lidar systems allows the use of optical location methods to detect and track moving objects in the atmosphere. This is primarily related to unmanned aerial vehicles (UAVs), which are widely used in many areas of human activity. This paper describes an experimental setup that makes it possible to detect a moving object in the atmosphere at a distance of more than 1 km, determine the distance to it, and automatically track it. The installation consists of a matrix photodetector of the visible and IR ranges, an active illumination source in the form of an IR laser diode emitting at a wavelength of λ = 808 nm with an output power of 30 W, and an IR lidar module with an energy per pulse of up to 15 mJ, emitting at a wavelength of λ = 1540 nm. It is shown that a combination of passive and active optical methods makes it possible to detect moving objects in the atmosphere, such as aerosol clouds or UAVs. For the automatic detection of moving objects of various types in the process of image processing in the visible and IR ranges, deep learning methods (convolutional neural networks) are used. With the help of the described installation, the linear dimensions of UAVs were estimated on routes of up to 1 km.

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Funding

This study was carried out in the framework of State Assignment of the Ministry of Science and Higher Education of the Russian Federation (registration number 122040500060–4), supported by a program of fundamental scientific research of the state academies of sciences for 2013–2020 (registration number AAAA-A18-118112290069-6) and grant no. 19-29-06009 mk of the Russian Foundation for Basic Research.

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Fufurin, I.L., Vintaikin, I.B., Nazolin, A.L. et al. Optical Methods for Detecting and Tracking Moving Objects in the Atmosphere. Russ. J. Phys. Chem. B 16, 483–491 (2022). https://doi.org/10.1134/S1990793122030034

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