Information fusion and reconstruction of key sensors in a flight control system in constant wind field based on two stage EKF

He Qizhi, Weiguo Zhang, Xiaoxiong Liu, Jinglong Liu

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

5 Scopus citations

Abstract

Kalman filter is of importance in information fusion and reconstruction of key sensors in a flight control system. Two stage kalman filter is able to solve the filtering problem which caused by an unknown constant bias in a filtering model. Extended kalman filter is one simple but effective method to deal with nonlinear system filtering problem. In this paper, constant wind field is regarded as the unknown constant bias in trajectory velocity measurement innovatively. Employing two stage extended kalman filter (TSEKF) realizes information fusion of key sensors in a flight control system. When air velocity, angle of attack and angle of sideslip sensors are working, TSEKF realizes estimations of air velocity, angle of attack, angle of sideslip and wind velocity. When they are out of work, TSEKF realizes information reconstruction of air velocity, angle of attack, angle of sideslip.

Original languageEnglish
Title of host publicationCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages718-724
Number of pages7
ISBN (Electronic)9781467383189
DOIs
StatePublished - 20 Jan 2017
Event7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China
Duration: 12 Aug 201614 Aug 2016

Publication series

NameCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/TerritoryChina
CityNanjing, Jiangsu
Period12/08/1614/08/16

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