Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1620
Title: A Kalman filtering algorithm for the estimation of chirp signals in Gaussian noise [articol]
Authors: Gál, János
Câmpeanu, Andrei
Naforniţă, Ioan
Subjects: Kalman filter
Polynomial phase signals
Linear state model
Parametric identification
Issue Date: 2007
Publisher: Timişoara : Editura Politehnica
Citation: Gál, János. A Kalman filtering algorithm for the estimation of chirp signals in Gaussian noise. Timişoara: Editura Politehnica, 2007
Series/Report no.: Seria electronică şi telecomunicaţii;Tom 52(66), fasc 2 (2007)
Abstract: The paper addresses the problem of estimating the parameters of polynomial phase signals (PPS) embedded in Gaussian noise. We consider an estimation method based on an approximate linear state space representation of the polynomial phase signal. This approach offers the opportunity to use a standard Kalman filtering procedure in view to estimate the parameters of PPS signals. Procedure simulations were made on linear chirp sinusoids with time-varying amplitude and are consistent with the theoretical approach. The paper presents the most important results.
URI: http://localhost:8080/xmlui/handle/123456789/1620
Appears in Collections:Articole stiintifice/Scientific articles

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