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Authors: Ali Asadian 1 ; Behzad Moshiri 1 ; Ali Khaki Sedigh 2 and Caro Lucas 3

Affiliations: 1 University of Tehran, Iran, Islamic Republic of ; 2 University of K.N.T, Iran, Islamic Republic of ; 3 School of Cognitive Sciences, Institute for Studies on Theoretical Physics and Mathematics, Iran, Islamic Republic of

ISBN: 972-8865-29-5

Keyword(s): Genetic optimization, Adaptive Network based Fuzzy Inference System (ANFIS), Global Positioning System (GPS), Inertial Navigation System (INS).

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: A new concept regarding to the GPS/INS integration, based on artificial intelligence here is presented. Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, an INS/GPS integration method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed in literature. During the availability of GPS signal, the ANFIS is trained to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. As ANFIS will be employed in real time applications, the change in the system parameters (e.g., the number of membership functions, the step size, and step increase and decrease rates) to achieve the minimum training error during each time period is automated. This paper introd uces a genetic optimization algorithm that is used to update the ANFIS parameters with the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS Integration in comparison with conventional ANFIS specially in the cases when facing satellites’ outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation. (More)

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Paper citation in several formats:
Asadian A.; Moshiri B.; Khaki Sedigh A.; Lucas C. and (2005). GA BASED DATA FUSION APPROACH IN AN INTELLIGENT INTEGRATED GPS/INS SYSTEM.In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 972-8865-29-5, pages 216-221. DOI: 10.5220/0001171802160221

@conference{icinco05,
author={Ali Asadian and Behzad Moshiri and Ali {Khaki Sedigh} and Caro Lucas},
title={GA BASED DATA FUSION APPROACH IN AN INTELLIGENT INTEGRATED GPS/INS SYSTEM},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2005},
pages={216-221},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001171802160221},
isbn={972-8865-29-5},
}

TY - CONF

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - GA BASED DATA FUSION APPROACH IN AN INTELLIGENT INTEGRATED GPS/INS SYSTEM
SN - 972-8865-29-5
AU - Asadian, A.
AU - Moshiri, B.
AU - Khaki Sedigh, A.
AU - Lucas, C.
PY - 2005
SP - 216
EP - 221
DO - 10.5220/0001171802160221

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