TY - GEN
T1 - Dynamic, noisy channel deconvolution
T2 - 13th International Congress on Sound and Vibration 2006, ICSV 2006
AU - Roan, Michael J.
AU - Gramann, Mark
PY - 2006
Y1 - 2006
N2 - Blind Deconvolution (BDC) algorithms typically assume a noiseless signal model, and a stationary signal propagating through a static channel. In real world systems this is almost never the case (e.g. the problem of interest in this paper: a noisy multipath propagation environment where the source and receiver are moving). In such cases, it is proposed that model-based techniques be applied to incorporate further a priori information about the system into the existing blind processing framework. The significant original contributions of this work are as follows: First, a modified formulation of the extended Kalman filter (EKF) is developed that allows incorporation of a priori information into gradient-based blind processing algorithms. This formulation is then applied to the existing Natural Gradient BDC algorithm. Finally, simulation results are presented that suggest significant improvement in signal recovery performance through application of the modified EKF to the NG BDC algorithm for dynamic noisy channels. Copyright
AB - Blind Deconvolution (BDC) algorithms typically assume a noiseless signal model, and a stationary signal propagating through a static channel. In real world systems this is almost never the case (e.g. the problem of interest in this paper: a noisy multipath propagation environment where the source and receiver are moving). In such cases, it is proposed that model-based techniques be applied to incorporate further a priori information about the system into the existing blind processing framework. The significant original contributions of this work are as follows: First, a modified formulation of the extended Kalman filter (EKF) is developed that allows incorporation of a priori information into gradient-based blind processing algorithms. This formulation is then applied to the existing Natural Gradient BDC algorithm. Finally, simulation results are presented that suggest significant improvement in signal recovery performance through application of the modified EKF to the NG BDC algorithm for dynamic noisy channels. Copyright
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M3 - Conference contribution
AN - SCOPUS:84883370728
SN - 9781627481502
T3 - 13th International Congress on Sound and Vibration 2006, ICSV 2006
SP - 4697
EP - 4704
BT - 13th International Congress on Sound and Vibration 2006, ICSV 2006
Y2 - 2 July 2006 through 6 July 2006
ER -