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Array covariance error measurement in adaptive source estimation
Pérez Neira, Ana Isabel; Lagunas Hernandez, Miguel A.
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
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.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
Kalman filtering
Kalman filters
Adaptive filters
Array signal processing
Parameter estimation
Kalman, Filtratge de

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