Student's t-Filters for Noise Scale Estimation

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date

2019-02-01

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Department of Electrical Engineering and Automation

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en

Pages

5

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IEEE Signal Processing Letters, Volume 26, issue 2, pp. 352-356

Abstract

In this letter, we analyze certain student's t-filters for linear Gaussian systems with misspecified noise covariances. It is shown that under appropriate conditions, the filter both estimates the state and re-scales the noise covariance matrices in a Kullback-Leibler optimal fashion. If the noise covariances are misscaled by a common scalar, then the re-scaling is asymptotically exact. We also compare the student's t.-filter scale estimates to the maximum-likelihood estimates. Simulations demonstrating the results on the Wiener velocity model are provided.

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Keywords

Kalman, Kalman filtering, Variances, model mis-specification, noise covariance estimation, student's t-filtering

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DOI

10.1109/LSP.2018.2889440

Citation

Tronarp, F, Karvonen, T & Särkkä, S 2019, ' Student's t-Filters for Noise Scale Estimation ', IEEE Signal Processing Letters, vol. 26, no. 2, 8606947, pp. 352-356 . https://doi.org/10.1109/LSP.2018.2889440

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https://urn.fi/URN:NBN:fi:aalto-201903052170

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[article-cris] Sähkötekniikan korkeakoulu / ELEC