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Radome slope estimation in flight using fuzzy adaptive multiple model for active homing missile

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

Abstract

For homing missile guidance system in there dimensional engagement scenarios, a new filter structure using fuzzy adaptive multiple model (FAMM) algorithm, based on extended Kalman filter (EKF), for estimating both the radome slope and guidance information is proposed to reduce the influence induced by radome and enhance the system performance. The radome slopes are modeled as a series of possible configurations which the multiple model algorithm is used to get the model match degree based on. The new filtering algorithm includes a fuzzy inference system which adjusted the adome slope model on line to reduce the error of estimation. Simulation results indicate that the proposed filter structure can estimate the radome slope availably and improve the guidance system performance.

Original languageEnglish
Title of host publicationICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments
Pages41017-41022
Number of pages6
DOIs
StatePublished - 2009
Event9th International Conference on Electronic Measurement and Instruments, ICEMI 2009 - Beijing, China
Duration: 16 Aug 200919 Aug 2009

Publication series

NameICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments

Conference

Conference9th International Conference on Electronic Measurement and Instruments, ICEMI 2009
Country/TerritoryChina
CityBeijing
Period16/08/0919/08/09

Keywords

  • Extended Kalman filter
  • Fuzzy inference
  • Multiple model
  • Radome estimation

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