Adaptive Kalman filter with multiple fading factors for UAV state estimation

Chingiz Hajiyev*, Halil Ersin Söken

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

In general case, as an algorithm for estimating the parameters of a linear system, Kalman filter can be utilized without any problem. However, when there is a malfunction in the estimation system, the filter fails and the outputs become inaccurate. In this paper, an Adaptive Kalman Filter with multiple fading factors based gain correction for the case of malfunctions in the estimation system is presented. By the use of an adaptive matrix constituted of multiple fading factors, faulty measurements are taken into consideration with small weight and the estimation errors are corrected without affecting the good estimation characteristic of the remaining process. Adaptive Kalman Filter algorithm is tested by simulations for the implementation in the navigation system of an UAV platform. The filter performance has been evaluated for different kinds of measurement malfunctions.

Original languageEnglish
Title of host publicationSAFEPROCESS'09 - 7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Systems, Proceedings
Pages77-82
Number of pages6
DOIs
Publication statusPublished - 2009
Event7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Systems, SAFEPROCESS'09 - Barcelona, Spain
Duration: 30 Jun 20093 Jul 2009

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
ISSN (Print)1474-6670

Conference

Conference7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Systems, SAFEPROCESS'09
Country/TerritorySpain
CityBarcelona
Period30/06/093/07/09

Keywords

  • Adaptive algorithms
  • Estimation parameters
  • Kalman filters

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