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The vision-based relative navigation using improved adaptive cubature huber-based filtering

  • Harbin Institute of Technology

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

Abstract

This paper presents the adaptive cubature Huber-based filtering(ACHF) algorithm which is applied to vision-based relative navigation between two unmanned aerial vehicles designated leader and follower. The proposed ACHF algorithm makes use of the Huber technique to modify the measurement update equations of the conventional cubature kalman filtering. Furthermore, the covariance matching technique is adopted to adjust the covariance matrices of the process noises and measurement noises online. The ACHF algorithm can estimate the precise relative navigation informations. Therefore, the proposed ACHF algorithm is robust to the non-Gaussian random measurement error. Simulation results show the superiority of the proposed ACHF algorithm in robustness and accuracy compared with the EKF, CKF and CHF algorithm.

Original languageEnglish
Title of host publication21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624104633
DOIs
StatePublished - 2017
Event21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017 - Xiamen, China
Duration: 6 Mar 20179 Mar 2017

Publication series

Name21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

Conference

Conference21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017
Country/TerritoryChina
CityXiamen
Period6/03/179/03/17

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