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An Augmented Strapdown Inertial Navigation System using Jerk and Jounce of Motion for a Flying Robot

Published online by Cambridge University Press:  08 March 2017

Milad Bayat  and
MA Amiri Atashgah
Milad Bayat
Affiliation:
(Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran)
MA Amiri Atashgah*
Affiliation:
(Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran)
*
(E-mail: [email protected])
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Abstract

This paper offers an algorithm for enhancement of positioning accuracy of a quad-rotor flying robot, based on jerk and jounce of motion. The suggested method utilises the first and second numerical derivatives of the vehicle's acceleration and augments the mathematical model in the estimation process. For this purpose, the Kalman Filter (KF) is implemented for integration of a Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS). The required data are collected from a low-cost/quality Micro Electromechanical Sensors (MEMS) during an assisted flight. For increasing the precision and accuracy of the collected data, all instruments including accelerometers, gyroscopes and magnetometers are calibrated before the experiments. Moreover, to reduce and limit the measurement noises of the MEMS sensor, a low-pass filter is applied; this is while sensors in the autopilot are affected by high levels of noise and drift, which makes them inappropriate for accurate positioning. The experimental results exhibit an improvement in positioning and altitude sensing through augmentation of the loosely coupled SINS/GNSS navigation method.

Keywords

Inertial NavigationSINS/GNSS IntegrationJerk and JounceFlying Robot
Type
Research Article
Information
The Journal of Navigation , Volume 70 , Issue 4 , July 2017 , pp. 907 - 926
Copyright
Copyright © The Royal Institute of Navigation 2017 

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