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Line of sight rate estimation of strapdown imaging guidance system based on Unscented Kalman Filter

  • Harbin Institute of Technology

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

Abstract

Models of the strapdown imaging guidance system are derived and corresponding estimation problem is considered in this paper. In comparison with the conventional imaging guidance systems, there are high nonlinearity in both process and measurement models, and measurement is more seriously corrupted by noise since wider instantaneous field of view for the stapdown imaging seeker. Considering these properties, the Unscented Kalman Filter (UKF) is applied to estimate line of sight (LOS) rate. The UKF propagates statistics of random variable more accurately than the Extended Kalman Filter (EKF) does for nonlinear system. Furthermore, the UKF avoids calculating Jacobian matrices which are complicated usually, and sometimes singular and thus infeasible for the EKF. At the last, Monte Carlo simulations are performed, and results show that the UKF is superior to the EKF for the strapdown imaging guidance system.

Original languageEnglish
Title of host publication2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
PublisherIEEE Computer Society
Pages1574-1578
Number of pages5
ISBN (Electronic)0780390911
ISBN (Print)078039092X, 9780780390928
DOIs
StatePublished - 2005
EventInternational Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China
Duration: 18 Aug 200521 Aug 2005

Publication series

Name2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Volume3

Conference

ConferenceInternational Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/TerritoryChina
CityGuangzhou
Period18/08/0521/08/05

Keywords

  • LOS rate
  • Nonlinear estimation
  • Strapdown imaging guidance
  • Unscented Kalman Filter

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