Adaptive filter for linear systems with generalized unknown disturbance in measurements

Yanbo Yang, Yuemei Qin, Yan Liang, Quan Pan, Feng Yang

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

5 Scopus citations

Abstract

The paper presents the problem of state estimation of linear stochastic time-varying system with generalized unknown disturbance (GUD) existing in the measurements. Such GUD can reflect the effects of sensor bias, deception jamming, navigation bias and so on. An upper-bound filter (UBF) is designed for such systems, and its optimal parameters are derived so that the minimum upper-bounds filter (MUBF) is obtained. The simulation about tracking a target via a biased sensor shows the effectiveness of the proposed filter.

Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Information Fusion, FUSION 2013
Pages1336-1341
Number of pages6
StatePublished - 2013
Event16th International Conference of Information Fusion, FUSION 2013 - Istanbul, Turkey
Duration: 9 Jul 201312 Jul 2013

Publication series

NameProceedings of the 16th International Conference on Information Fusion, FUSION 2013

Conference

Conference16th International Conference of Information Fusion, FUSION 2013
Country/TerritoryTurkey
CityIstanbul
Period9/07/1312/07/13

Keywords

  • Adaptive filtering
  • discrete time systems
  • generalized unknown disturbance

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