Sensor Fusion Using Kalman Filter for a Quadrotor-Attitude Estimation

Samir Ayman

ISBN 10: 3659854689 / ISBN 13: 9783659854682

Published by LAP LAMBERT Academic Publishing Mär 2016, 2016

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Quad rotors are types of unmanned air vehicles that became an attractive topic to an enormous number of people worldwide. This book focuses on sensor fusion of low-cost inertial sensors: a tri-axis accelerometer, a tri-axis gyroscope and a tri-axis magnetometer. Three types of filters were implemented in this book: two models of linear complementary filter (LCF), two models of linear Kalman filter (KF) and a quaternion-based extended Kalman filter (EKF). A total of five filter models were tested and verified using experimental data sets through three distinct scenarios. Six different data sets were chosen, each with antithetic characteristics, to test the filters on them. On the basis of the results of this research, it can be concluded that taking into consideration accelerometer bias improves the performance of the filter. KF shows the best performance as it combines the characteristics of short computing time and accurate estimation results suiting the aim of the book which is to allow the quad rotor to hover.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 200 pp. Englisch.

Seller Inventory # 9783659854682

Bibliographic Details

• Title: Sensor Fusion Using Kalman Filter for a Quadrotor-Attitude Estimation
• Publisher: LAP LAMBERT Academic Publishing Mär 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3659854689
• ISBN 13: 9783659854682
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 13D millimeters 220 millimeters width by 150 millimeters height by 13 millimeters depth
• Weight: 316 grams

About this title

Synopsis

Quad rotors are types of unmanned air vehicles that became an attractive topic to an enormous number of people worldwide. This book focuses on sensor fusion of low-cost inertial sensors: a tri-axis accelerometer, a tri-axis gyroscope and a tri-axis magnetometer. Three types of filters were implemented in this book: two models of linear complementary filter (LCF), two models of linear Kalman filter (KF) and a quaternion-based extended Kalman filter (EKF). A total of five filter models were tested and verified using experimental data sets through three distinct scenarios. Six different data sets were chosen, each with antithetic characteristics, to test the filters on them. On the basis of the results of this research, it can be concluded that taking into consideration accelerometer bias improves the performance of the filter. KF shows the best performance as it combines the characteristics of short computing time and accurate estimation results suiting the aim of the book which is to allow the quad rotor to hover.

About the Author

Samir Ayman Abdel Aal, born in Cairo on the 2nd of March 1993. Graduated with a BSc. in Mechatronics Engineering at the German University in Cairo in July 2015. Currently working as an Account Manager at IBM, Cairo, Egypt.