Open AccessKalman Filter Based Sensor Fusion for Altitude Estimation of Aerial Vehicle
Author(s) -
Muhammad Bashir,
Fahad Mumtaz Malik,
Zeeshan Ali Akbar,
Muhammad Uzair
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/853/1/012034
Subject(s) - kalman filter , altitude (triangle) , inertial measurement unit , sensor fusion , barometer , computer science , initialization , extended kalman filter , filter (signal processing) , remote sensing , artificial intelligence , computer vision , geography , mathematics , meteorology , geometry , programming language
Stabilization of Aerial Vehicles requires altitude estimation. In this paper sensor fusion method is developed for aerial vehicles which focuses on estimation of the altitude. Altitude measurement using sensors is too noisy and biased so Kalman filter based sensor fusion is used to estimate altitude. The proposed method is divided into two parts: attitude estimation and altitude estimation. The method is implemented using IMU and barometer sensors. The results show that altitude is estimated accurately and errors are modelled in few seconds after initialization.