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Constrained Unscented Particle Filter for SINS/GNSS/ADS Integrated Airship Navigation in the Presence of Wind Field Disturbance.
Gao, Zhaohui; Mu, Dejun; Zhong, Yongmin; Gu, Chengfan.
Afiliação
  • Gao Z; School of Automatics, Northwestern Polytechnical University, Xi'an 710072, China. alexandergao@mail.nwpu.edu.cn.
  • Mu D; School of Automatics, Northwestern Polytechnical University, Xi'an 710072, China. mudejun@nwpu.edu.cn.
  • Zhong Y; School of Engineering, RMIT University, Bundoora, Melbourne 3083, Australia. yongmin.zhong@rmit.edu.au.
  • Gu C; Department of Mechanical Engineering, University of Melbourne, Parkville, Melbourne 3010, Australia. chengfan.gu@gmail.com.
Sensors (Basel) ; 19(3)2019 Jan 24.
Article em En | MEDLINE | ID: mdl-30682782
Due to the disturbance of wind field, it is difficult to achieve precise airship positioning and navigation in the stratosphere. This paper presents a new constrained unscented particle filter (UPF) for SINS/GNSS/ADS (inertial navigation system/global navigation satellite system/atmosphere data system) integrated airship navigation. This approach constructs a wind speed model to describe the relationship between airship velocity and wind speed using the information output from ADS, and further establishes a mathematical model for SINS/GNSS/ADS integrated navigation. Based on these models, it also develops a constrained UPF to obtain system state estimation for SINS/GNSS/ADS integration. The proposed constrained UPF uses the wind speed model to constrain the UPF filtering process to effectively resist the influence of wind field on the navigation solution. Simulations and comparison analysis demonstrate that the proposed approach can achieve optimal state estimation for SINS/GNSS/ADS integrated airship navigation in the presence of wind field disturbance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China