Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace: http://hdl.handle.net/2117/88453

Título:	Array covariance error measurement in adaptive source estimation
Autor/a:	Pérez Neira, Ana Isabel; Lagunas Hernandez, Miguel A.
Otros autores:	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. A&MP - Grup de Processament d'Arrays i Sistemes Multicanal
Abstract:	The small error approximation is used to derive a linear relationship between the source parameters (i.e. power levels and directions of arrival) and a measurement of the covariance error matrix, defined as the difference between a nonparametric consistent estimate of the spectral density matrix and a covariance model from the scenario parameters. The resulting framework allows the design of a Kalman-like algorithm which provides a simultaneous and adaptive estimation of the source parameter, no matter what the source waveform or modulation. Good performance is expected, mainly in the presence of sensors malfunctioning, low signal-to-noise ratio, etc.
Abstract:	Peer Reviewed
Materia(s):	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació Kalman filtering Kalman filters Adaptive filters Array signal processing Parameter estimation Kalman, Filtratge de
Derechos:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Tipo de documento:	info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/conferenceObject
Compartir:

Mostrar el registro completo del ítem