UAV attitude, heading, and wind estimation using GPS/INS and an air data system

Matthew Rhudy, Trenton Larrabee, Haiyang Chao, Yu Gu, Marcello R. Napolitano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

42 Scopus citations

Abstract

A new attitude, heading, and wind estimation algorithm is proposed, which incorporates measurements from an air data system to properly relate predicted attitude information with aircraft velocity information. Experimental Unmanned Aerial Vehicle (UAV) flight data was used to validate the proposed approach. The experimental results demonstrated effective estimation of the roll, pitch, yaw, and heading angles, and provided a smoothed estimate of the angle of attack and sideslip angles. The wind estimation results were validated with respect to measurments provided by a local weather station. It was shown that this new method of attitude estimation is effective in distinguishing the yaw and heading angles of the aircraft, properly regulating the attitude estimates with air data system measurements, and provding a reasonable estimate of the local wind field.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control (GNC) Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Print)9781624102240
DOIs
StatePublished - 2013
EventAIAA Guidance, Navigation, and Control (GNC) Conference - Boston, MA, United States
Duration: Aug 19 2013Aug 22 2013

Publication series

NameAIAA Guidance, Navigation, and Control (GNC) Conference

Other

OtherAIAA Guidance, Navigation, and Control (GNC) Conference
CountryUnited States
CityBoston, MA
Period8/19/138/22/13

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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