Por favor, use este identificador para citar o enlazar este ítem: http://cicese.repositorioinstitucional.mx/jspui/handle/1007/1692
Efficiency evaluation of the unconditional maximum likelihood estimator for near-field source DOA estimation
JOSE GUADALUPE ARCEO OLAGUE
DAVID HILARIO COVARRUBIAS ROSALES
JOSE MARTIN LUNA RIVERA
Acceso Abierto
Atribución-NoComercial-SinDerivadas
dx.doi.org/10.4218/etrij.06.0106.0006
Near-field source localization, DOA, UML estimator, Sensor array
"In this paper, we address the problem of closely spaced source localization using sensor array processing. In particular, the performance efficiency (measured in terms of the root mean square error) of the unconditional maximum likelihood (UML) algorithm for estimating the direction of arrival (DOA) of near-field sources is evaluated. Four parameters are considered in this evaluation: angular separation among sources, signal-to-noise ratio (SNR), number of snapshots, and number of sources (multiple sources). Simulations are conducted to illustrate the UML performance to compute the DOA of sources in the near-field. Finally, results are also presented that compare the performance of the UML DOA estimator with the existing multiple signal classification approach. The results show the capability of the UML estimator for estimating the DOA when the angular separation is taken into account as a critical parameter. These results are consistent in both low SNR and multiple-source scenarios."
Electronics and Telecommunications Research Institute (ETRI)
2006
Artículo
ETRI Journal, Vol. 28, No. 6, Págs. 761-769
Inglés
Arceo Olague,J.,Covarrubias Rosales,D.,Luna Rivera,J.2006.Efficiency Evaluation of the Unconditional Maximum Likelihood Estimator for Near-Field DOA Estimation.ETRI Journal,28(6),761-769.doi:10.4218/etrij.06.0106.0006
ELECTRÓNICA
Versión publicada
publishedVersion - Versión publicada
Aparece en las colecciones: Artículos - Electrónica y Telecomunicaciones

Cargar archivos:


Fichero Tamaño Formato  
90211.pdf4.96 kBAdobe PDFVisualizar/Abrir