Helicopter classification with a high resolution LFMCW radar

Muñoz Ferreras, José María ORCID: https://orcid.org/0000-0003-1929-3934, Pérez Martínez, Félix ORCID: https://orcid.org/0000-0001-5857-1082 and Burgos García, Mateo ORCID: https://orcid.org/0000-0002-5836-4291 (2009). Helicopter classification with a high resolution LFMCW radar. "IEEE Transactions on Aerospace and Electronic systems", v. 45 (n. 4); pp. 1373-1384. ISSN 0018-9251. https://doi.org/10.1109/TAES.2009.5310305.

Descripción

Título: Helicopter classification with a high resolution LFMCW radar
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: IEEE Transactions on Aerospace and Electronic systems
Fecha: Octubre 2009
ISSN: 0018-9251
Volumen: 45
Número: 4
Materias:
ODS:
Palabras Clave Informales: Helicopters; radar; chirp modulation; blades; frequency modulation; signal resolution; bandwidth; robustness; signal to noise ratio; classification algorithms.
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Helicopter classification using a high resolution linear frequency modulated continuous wave (LFMCW) radar is addressed. A blade echo modelling for this radar system is derived, taking into account that the stop-and-go assumption is not longer applicable. The standard classification schemes based on the L/N-quotient and the evenness of the number of blades are easily reproduced in this high resolution context, although two main advantages are added: a high pulse repetition frequency (PRF) to acquire the Doppler bandwidth is no longer necessary, and the time for which we receive returned signal from the target may be maximized. On the other hand, a characteristic critical classification problem, for which the standard approaches do not properly work, is presented. Two classification schemes are proposed for this situation, the first one based on coherent matched masks and the second one based on incoherent masks where a robustness parameter has also been defined. Identification probabilities as a function of the signal-to-noise ratio (SNR) are obtained in order to characterize the performance of both techniques. Real data validate both the derived model and the proposed classification algorithms.

Más información

ID de Registro: 80738
Identificador DC: https://oa.upm.es/80738/
Identificador OAI: oai:oa.upm.es:80738
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5484186
Identificador DOI: 10.1109/TAES.2009.5310305
URL Oficial: https://ieeexplore.ieee.org/document/5310305
Depositado por: Biblioteca ETSI Telecomunicación
Depositado el: 18 Mar 2024 11:30
Ultima Modificación: 12 Nov 2025 00:00