Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Approximate Diagonalized Covariance Matrix for Signals with Correlated Noise
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-1971-4295
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
University of Groningen, Centre for Theoretical Physics, Zernike Institute for Advanced Materials.
2016 (Engelska)Ingår i: Proceedings of the 19th International Conference of Information Fusion, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 521-527Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This paper proposes a diagonal covariance matrix approximation for Wide-Sense Stationary (WSS) signals with correlated Gaussian noise. Existing signal models that incorporate correlations often require regularization of the covariance matrix, so that the covariance matrix can be inverted. The disadvantage of this approach is that matrix inversion is computational intensive and regularization decreases precision. We use Bienayme's theorem to approximate the covariance matrix by a diagonal one, so that matrix inversion becomes trivial, even with nonuniform rather than only uniform sampling that was considered in earlier work. This approximation reduces the computational complexity of the estimator and estimation bound significantly. We numerically validate this approximation and compare our approach with the Maximum Likelihood Estimator (MLE) and Cramer-Rao Lower Bound (CRLB) for multivariate Gaussian distributions. Simulations show that our approach differs less than 0.1% from this MLE and CRLB when the observation time is large compared to the correlation time. Additionally, simulations show that in case of non-uniform sampling, we increase the performance in comparison to earlier work by an order of magnitude. We limit this study to correlated signals in the time domain, but the results are also applicable in the space domain.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE), 2016. s. 521-527
Nyckelord [en]
Signal processing, approximate estimation
Nationell ämneskategori
Reglerteknik Signalbehandling
Identifikatorer
URN: urn:nbn:se:liu:diva-130162ISI: 000391273400071ISBN: 978-0-9964527-4-8 (tryckt)OAI: oai:DiVA.org:liu-130162DiVA, id: diva2:948531
Konferens
19th International Conference of Information Fusion, Heidelberg, Germany, July 5-8 2016
Forskningsfinansiär
VetenskapsrådetTillgänglig från: 2016-07-12 Skapad: 2016-07-12 Senast uppdaterad: 2017-02-03Bibliografiskt granskad

Open Access i DiVA

fulltext(151 kB)140 nedladdningar
Filinformation
Filnamn FULLTEXT02.pdfFilstorlek 151 kBChecksumma SHA-512
1c9715ea79bdc8d8fde6852ea6171102da73cf9c77ff5e8880496c84d9a05bd73501573b9ea02893a7508e6315feca39700bee9b2fae12ae31a4d4b309641604
Typ fulltextMimetyp application/pdf

Övriga länkar

Link to publication

Sök vidare i DiVA

Av författaren/redaktören
Dil, BramHendeby, GustafGustafsson, Fredrik
Av organisationen
ReglerteknikTekniska fakulteten
ReglerteknikSignalbehandling

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 184 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

isbn
urn-nbn

Altmetricpoäng

isbn
urn-nbn
Totalt: 519 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf