DocumentCode :
2140362
Title :
Myopic deconvolution combining Kalman filter and tracking control
Author :
Sarri, P. ; Thomas, G. ; Sekko, E. ; Neveux, P.
Author_Institution :
Lab. d´´Autom. Ind., Inst. Nat. des Sci. Appliquees, Villeurbanne, France
Volume :
3
fYear :
1998
fDate :
12-15 May 1998
Firstpage :
1833
Abstract :
In this paper, we propose a deconvolution method based on discrete-time optimal control. By combining Kalman filtering with optimal control, we state the problem in terms of a tracking problem. This leads to solve a set of recurrent equations, including in particular a matrix Riccati equation. We present a method that transforms the solution of these recurrent equations in that of a linear system of equations. Once the linear system has been set up, the deconvolution procedure becomes very fast, and permits on-line deconvolution. It is also possible to use the discrete impulse response, and perform blind deconvolution. This technique includes an L2 or H optimal filter. Numerical examples illustrate the robustness of the procedure
Keywords :
H control; Kalman filters; Riccati equations; deconvolution; discrete time systems; linear systems; matrix algebra; signal restoration; time optimal control; tracking filters; transient response; H optimal filter; Kalman filter; L2 optimal filter; discrete impulse response; discrete-time optimal control; linear system; matrix Riccati equation; myopic deconvolution; recurrent equations; robustness; tracking control; Automatic control; Deconvolution; Discrete transforms; Gaussian noise; Industrial control; Kalman filters; Linear systems; Optimal control; Riccati equations; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
ISSN :
1520-6149
Print_ISBN :
0-7803-4428-6
Type :
conf
DOI :
10.1109/ICASSP.1998.681819
Filename :
681819
Link To Document :
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