GPS-INS Integration Algorithm for Autonomous Vehicle Using Loosely Coupled Integration Architecture

Inertial measurement unit (IMU) has been widely used for autonomous vehicles navigation. The accuracy of IMU specifies the performance of the inertial navigation system (INS).The errors in the INS are mainly due to the IMU inaccuracies, initial alignment, computational errors and approximations in t...

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Bibliographic Details
Published in:Applied Mechanics and Materials Vol. 390; pp. 506 - 511
Main Authors: Li, Zhong Jian, Iqbal, Rashid, Badshah, Khan
Format: Journal Article
Language:English
Published: Zurich Trans Tech Publications Ltd 30.08.2013
Subjects:
Kalman Filtering
Inertial Navigation System (INS)
GPS
Autonomous Vehicles
Loosely Coupled Approach
ISBN:9783037858332, 3037858338
ISSN:1660-9336, 1662-7482, 1662-7482
Online Access:Get full text
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Summary:Inertial measurement unit (IMU) has been widely used for autonomous vehicles navigation. The accuracy of IMU specifies the performance of the inertial navigation system (INS).The errors in the INS are mainly due to the IMU inaccuracies, initial alignment, computational errors and approximations in the system equations. These errors are further integrated over time due to the dead-reckoning nature of the INS, which leads to unacceptable results. These errors need an accurate estimation for high precision navigation. INS is integrated with Global Positioning System (GPS) to estimate the errors and enhance the navigation capability of the INS. Linearized Kalman Filter (LKF) is proposed for estimating the errors in the low cost INS using Loosely Coupled integration approach, which is opted for its simplicity and robustness. Prediction part of the LKF is used during the GPS lag for errors estimation, which is found very effective for low cost sensors. The resulting GPS-INS integration algorithm is evaluated on simulated Autonomous vehicle trajectory, generated from 6-DOF model. The integrated system limits the attitude errors less than 0.1 deg and velocity errors of the order of 0.003 meter per second. Furthermore, it provides an optimal navigation solution than can be achieved from individual systems.
Bibliography:Selected, peer reviewed papers from the 2013 4th International Conference on Mechanical and Aerospace Engineering (ICMAE 2013), July 20-21, 2013, Moscow, Russia
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ISBN:9783037858332
3037858338
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.390.506