Time-domain filtering for estimation of linear systems with colored noises using recent finite measurements

Hyun Duck Choi, Choon Ki Ahn, Myo Taeg Lim

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

To date, finite impulse response (FIR) filters have been proposed to estimate linear systems with white Gaussian noises, but to the best of our knowledge, no solution exists for linear systems with colored noises. In this paper, we propose a new FIR filter to estimate linear state-space models with both process and measurement noises through state augmentation. In addition, we suggest a modified form of the colored-noise FIR filter to deal with the computational burden and singularity problem. Numerical examples are presented to describe the effectiveness of the colored-noise FIR filter.

Original languageEnglish
Pages (from-to)2792-2797
Number of pages6
JournalMeasurement: Journal of the International Measurement Confederation
Volume46
Issue number8
DOIs
Publication statusPublished - 2013 Jun 21

Fingerprint

FIR filters
Colored Noise
Impulse Response
linear systems
Linear systems
Time Domain
Filtering
Linear Systems
Filter
Augmentation
Gaussian White Noise
State-space Model
estimates
noise measurement
random noise
Linear Space
Estimate
Linear Model
Singularity
Numerical Examples

Keywords

  • Colored noises
  • Finite impulse response (FIR) structure
  • Inverse partitioned matrix
  • State augmentation
  • State estimation

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Applied Mathematics

Cite this

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title = "Time-domain filtering for estimation of linear systems with colored noises using recent finite measurements",
abstract = "To date, finite impulse response (FIR) filters have been proposed to estimate linear systems with white Gaussian noises, but to the best of our knowledge, no solution exists for linear systems with colored noises. In this paper, we propose a new FIR filter to estimate linear state-space models with both process and measurement noises through state augmentation. In addition, we suggest a modified form of the colored-noise FIR filter to deal with the computational burden and singularity problem. Numerical examples are presented to describe the effectiveness of the colored-noise FIR filter.",
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AU - Choi, Hyun Duck

AU - Ahn, Choon Ki

AU - Lim, Myo Taeg

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Y1 - 2013/6/21

N2 - To date, finite impulse response (FIR) filters have been proposed to estimate linear systems with white Gaussian noises, but to the best of our knowledge, no solution exists for linear systems with colored noises. In this paper, we propose a new FIR filter to estimate linear state-space models with both process and measurement noises through state augmentation. In addition, we suggest a modified form of the colored-noise FIR filter to deal with the computational burden and singularity problem. Numerical examples are presented to describe the effectiveness of the colored-noise FIR filter.

AB - To date, finite impulse response (FIR) filters have been proposed to estimate linear systems with white Gaussian noises, but to the best of our knowledge, no solution exists for linear systems with colored noises. In this paper, we propose a new FIR filter to estimate linear state-space models with both process and measurement noises through state augmentation. In addition, we suggest a modified form of the colored-noise FIR filter to deal with the computational burden and singularity problem. Numerical examples are presented to describe the effectiveness of the colored-noise FIR filter.

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KW - Inverse partitioned matrix

KW - State augmentation

KW - State estimation

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