Neural networks for pattern recognition
Neural networks for pattern recognition
On-line learning in neural networks
On-line learning in neural networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Mathematical Methods for Neural Network Analysis and Design
Mathematical Methods for Neural Network Analysis and Design
Principles of Neurocomputing for Science and Engineering
Principles of Neurocomputing for Science and Engineering
Artificial Intelligence and Neural Networks; Steps toward Principled Integration
Artificial Intelligence and Neural Networks; Steps toward Principled Integration
Towards the automation of intelligent data analysis
Applied Soft Computing
New fuzzy wavelet neural networks for system identification and control
Applied Soft Computing
Design of anti-GPS for reasons of security
CIS'09 Proceedings of the international conference on Computational and information science 2009
In-car positioning and navigation technologies: a survey
IEEE Transactions on Intelligent Transportation Systems
An ANN embedded RTS smoother for an INS/GPS integrated Positioning and Orientation System
Applied Soft Computing
Intelligently tuned wavelet parameters for GPS/INS error estimation
International Journal of Automation and Computing
A simulation framework for UAV sensor fusion
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
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The Kalman filter (KF) has been implemented as the primary integration scheme of the global positioning system (GPS) and inertial navigation systems (INS) for many land vehicle navigation and positioning applications. However, it has been reported that KF-based techniques have certain limitations, which reflect on the position error accumulation during GPS signal outages. Therefore, this article exploits the idea of incorporating artificial neural networks to develop an alternative INS/GPS integration scheme, the intelligent navigator, for next generation land vehicle navigation and positioning applications. Real land vehicle test results demonstrated the capability of using stored navigation knowledge to provide real-time reliable positioning information for stand-alone INS-based navigation for up to 20min with errors less than 16m (as compared to 2.6km in the case of the KF). For relatively short GPS outages, the KF was superior to the intelligent navigator for up to 30s outages. In contrast, the intelligent navigator was superior to the KF when the length of GPS outages was extended to 90s. The average improvement of the intelligent navigator reached 60% in the latter scenario. The results presented in this article strongly indicate the potential of including the intelligent navigator as the core algorithm for INS/GPS integrated land vehicle navigation systems.