IIR deconvolution from noisy observations using Kalman filtering

Author

Bora, Siddharth Sankar ; Karuna, Yepuganti ; Dhuli, Ravindra ; Lall, Brejesh

Author_Institution

Dept. of ECE, Nat. Inst. of Technol., Warangal, India

fYear

2010

fDate

15-17 Dec. 2010

Firstpage

339

Lastpage

342

Abstract

In this paper, we reconstruct the input signal of an IIR filter from the noise corrupted output signal. We perform two operations parallely. One deconvolution and the other, noise removal. We show how to use Kalman filter to perform this task. We develop theory for a very general scenario of reconstructing an ARMA process from its noise corrupted IIR filtered output. We develop augmented state space equations combining the state space equations of the ARMA process and the IIR filter, which are required to apply Kalman filter. The simulation results show clear improvement in the signal-to-noise ratio.

Keywords

IIR filters; Kalman filters; autoregressive moving average processes; deconvolution; signal denoising; signal reconstruction; ARMA process; IIR deconvolution; IIR filter; Kalman filtering; augmented state space equations; noise corrupted IIR filtered output; noise removal; signal reconstruction; signal-to-noise ratio; Deconvolution; Equations; Kalman filters; Mathematical model; Noise measurement; Signal to noise ratio; Deconvolution; Kalman filtering; Noise Filtering;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal and Image Processing (ICSIP), 2010 International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4244-8595-6

Type

conf

DOI

10.1109/ICSIP.2010.5697494

Filename

5697494