Analysis of single Gaussian approximation of Gaussian mixtures in Bayesian filtering applied to mixed multiple-model estimation

Orguner U., Demirekler M.

INTERNATIONAL JOURNAL OF CONTROL, cilt.80, sa.6, ss.952-967, 2007 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 80 Sayı: 6
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1080/00207170701261952
  • Dergi Adı: INTERNATIONAL JOURNAL OF CONTROL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.952-967
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This paper examines the effect of the moment-matched single Gaussian approximation, which is made in various multiple-model filtering applications to approximate a Gaussian mixture, on the Bayesian filter performance. The estimation error caused by the approximation is analysed for both the prediction and the measurement updates of a Bayesian filter. An approximate formula is found for the covariance of the error caused by the approximation for a general Gaussian mixture with arbitrary components. The calculated error covariance is used for obtaining a mixed multiple-model estimation algorithm which has a performance near that of GPB2 with less computations.