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: |
![]() ![]() |