Trade studies on implementation of extended kalman filters for sUAS navigation

Takuma Nakamura, Eric Johnson

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

1 Scopus citations


THIS document describes the development and implementation of the extended Kalman filters (EKF) utilized for navigation algorithms of small unmanned aerial vehicles. The states of a vehicle and sensor biases are estimated using only on-board sensors and the knowledge of statistical properties of the sensor performance. An accelerometer, gyroscope, global positioning system, magnetometer, barometer, and pitot-statis system are used to estimate the position, velocity, and attitude of the vehicle, sensor biases, and the wind speed. The results of the Monte Carlo simulations with synthetic vehicle trajectory are provided for multiple scenarios. The discussion includes the trade studies on implementation regarding sensor placement, unknown local magnetic disturbances, filter design, and computational cost.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
StatePublished - Jan 1 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum


ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering


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