International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 6, No. 1, 8 Dec. 2013
Cover page and Table of Contents: PDF (size: 467KB)
New RLS Wiener Smoother for Colored Observation Noise in Linear Discrete-time Stochastic Systems
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Author(s)
Seiichi Nakamori
1,*
Index Terms
Discrete-Time Stochastic Systems, RLS Wiener Fixed-Point Smoother, Colored Observation Noise, Covariance Information, Filter
Abstract
In the estimation problems, rather than the white observation noise, there are cases where the observation noise is modeled by the colored noise process. In the observation equation, the observed value y(k) is given as a sum of the signal z(k)=Hx(k) and the colored observation noise v_c(k). In this paper, the observation equation is converted to the new observation equation for the white observation noise. In accordance with the observation equation for the white observation noise, this paper proposes new RLS Wiener estimation algorithms for the fixed-point smoothing and filtering estimates in linear discrete-time wide-sense stationary stochastic systems. The RLS Wiener estimators require the following information: (a) the system matrix for the state vector x(k); (b) the observation matrix H; (c) the variance of the state vector x(k); (d) the system matrix for the colored observation noise v_c(k); (e) the variance of the colored observation noise.
Cite This Paper
Seiichi Nakamori, "New RLS Wiener Smoother for Colored Observation Noise in Linear Discrete-time Stochastic Systems", International Journal of Information Technology and Computer Science(IJITCS), vol.6, no.1, pp.13-24, 2014. DOI:10.5815/ijitcs.2014.01.02
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