EM Modelling of Monostatic RCS for Different Complex Targets in the Near-Field Range: Experimental Evaluation for Traffic Applications

An evaluation of monostatic radar cross section (RCS) response in the near-field range was performed for several targets with different and complex topologies. The main objective was to provide and validate an efficient tool based on electromagnetic (EM) simulations to characterize a traffic scenari...

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Detalles Bibliográficos
Autores: Sánchez Olivares, Pablo|||0000-0002-7370-3095, Lozano Plata, Lorena|||0000-0002-0137-7868, Somolinos Yagüe, Álvaro|||0000-0001-6708-5406, Cátedra Pérez, Manuel Felipe|||0000-0003-0914-6391
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/60414
Acceso en línea:http://hdl.handle.net/10017/60414
https://dx.doi.org/10.3390/electronics9111890
Access Level:acceso abierto
Palabra clave:Telecomunicaciones
Telecommunication
Descripción
Sumario:An evaluation of monostatic radar cross section (RCS) response in the near-field range was performed for several targets with different and complex topologies. The main objective was to provide and validate an efficient tool based on electromagnetic (EM) simulations to characterize a traffic scenario. Thus, a novel method based on the combination of geometrical theory of diffraction (GTD) and physical optics (PO) was used to estimate RCS, and the results were compared with the method of moments (MoM) methodology. The simulations were xperimentally validated using a commercial vehicular frequency-modulated continuous wave (FMCW) radar at 24 GHz. With this simple measurement system, RCS measurements can be made using an easier and cheaper process to obtain RCS response in the near-field range, which is the most usual situation for traffic applications. A reasonable agreement between the measurements and the EM simulations was observed, validating the proposed methodology in order to efficiently characterize the RCS of targets typically found in real traffic scenarios.