Performance and stochastic stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

• Autorzy: Cenker Biçer , Levent Özbek , Hasan Erbay
• Języki publikacji: EN

Abstrakty

EN

In this paper, the stability of the adaptive fading extended Kalman filter with the matrix forgetting factor when applied to the state estimation problem with noise terms in the non–linear discrete–time stochastic systems has been analysed. The analysis is conducted in a similar manner to the standard extended Kalman filter’s stability analysis based on stochastic framework. The theoretical results show that under certain conditions on the initial estimation error and the noise terms, the estimation error remains bounded and the state estimation is stable. The importance of the theoretical results and the contribution to estimation performance of the adaptation method are demonstrated interactively with the standard extended Kalman filter in the simulation part.

Słowa kluczowe

EN

Kalman filter; Non-linear systems; Stability; Adaptive filtering

Kategorie tematyczne

• 37Hxx: Random dynamical systems

• Wydawca: De Gruyter Open
• Czasopismo: Open Mathematics
• Rocznik: 2016
• Tom: 14
• Numer: 1
• Strony: 934-945

Daty

wydano

2016-01-01

online

2016-11-17

Twórcy

autor

Cenker Biçer

• Statistics Department, Arts & Science Faculty, Kırıkkale University, 71450 Kırıkkale,,

autor

Levent Özbek

• Department of Statistics, Faculty of Science, Ankara University, 06100, Tandoğan, Ankara,,

autor

Hasan Erbay

• Computer Engineering Department, Engineering Faculty, Kırıkkale University, Yahşhan, 71450 Kırıkkale,,

Identyfikatory

DOI

10.1515/math-2016-0083