RADAR-BASED DETECTION AND RECOGNITION METHODOLOGY OF AUTONOMOUS SURFACE VEHICLES IN CHALLENGING MARINE ENVIRONMENT
| Autor: | Dmytro KORBAN, Oleksiy MELNYK, Oleg ONISHCHENKO, Serhii KURDIUK, Valerii SHEVCHENKO |
|---|---|
| Jazyk: | English<br />Polish |
| Rok vydání: | 2024 |
| Předmět: |
autonomous surface vehicles
object detection and ranging radar technology adverse weather conditions atmospheric interference environmental factors signal characteristics vessel particulars sensor performance adaptability shipping navigation influence factors detection accuracy Engineering (General). Civil engineering (General) TA1-2040 Transportation engineering TA1001-1280 |
| Zdroj: | Scientific Journal of Silesian University of Technology. Series Transport, Vol 122, Pp 111-127 (2024) |
| Druh dokumentu: | article |
| ISSN: | 0209-3324 2450-1549 |
| DOI: | 10.20858/sjsutst.2024.122.7 |
| Popis: | This paper presents a methodology that combines radar polarization selection and recognition techniques for navigating objects in atmospheric formations, with a special focus on unmanned surface vehicles (ASVs). The proposed technique utilizes the concept of an energy dissipation matrix to represent these objects as characteristic “shiny dots”. By strategically changing the polarization of the emitted and received electromagnetic waves, the resulting echo energy dissipation matrix is determined. This approach allows the formation of an intensity-based repository of atmospheric formations, which gives SRPC a complete set of tools to account for atmospheric conditions in radar identification of remote objects, including ASVs. The practical application of this technique extends to the improvement of a distinct class of shipborne radar systems optimized for ASVs and their specific navigation requirements. Ultimately, this technology bridges the gap between advanced radar technology and the emerging field of unmanned ground vehicles, providing safer and more proficient navigation in challenging weather conditions. |
| Databáze: | Directory of Open Access Journals |
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