Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Learning fuzzy knowledge from training examples
Proceedings of the seventh international conference on Information and knowledge management
Real-Time Systems and Software
Real-Time Systems and Software
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Uncertainty-Based Information: Elements of Generalized Information Theory
Uncertainty-Based Information: Elements of Generalized Information Theory
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Unsupervised adaptive neural-fuzzy inference system for solving differential equations
Applied Soft Computing
Expert Systems with Applications: An International Journal
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Intelligently tuned wavelet parameters for GPS/INS error estimation
International Journal of Automation and Computing
Prediction of liquefaction potential based on CPT up-sampling
Computers & Geosciences
A novel hybrid fusion algorithm to bridge the period of GPS outages using low-cost INS
Expert Systems with Applications: An International Journal
Optimization of Intelligent Approach for Low-Cost INS/GPS Navigation System
Journal of Intelligent and Robotic Systems
Hi-index | 0.00 |
The last two decades have shown an increasing trend in the use of positioning and navigation technologies in land vehicles. Most of the present navigation systems incorporate global positioning system (GPS) and inertial navigation system (INS), which are integrated using Kalman filtering (KF) to provide reliable positioning information. Due to several inadequacies related to KF-based INS/GPS integration, artificial intelligence (AI) methods have been recently suggested to replace KF. Various neural network and neuro-fuzzy methods for INS/GPS integration were introduced. However, these methods provided relatively poor positioning accuracy during long GPS outages. Moreover, the internal system parameters had to be tuned over time of the navigation mission to reach the desired positioning accuracy. In order to overcome these limitations, this study optimizes the AI-based INS/GPS integration schemes utilizing adaptive neuro-fuzzy inference system (ANFIS) by implementing, a temporal window-based cross-validation approach during the update procedure. The ANFIS-based system considers a non-overlap moving window instead of the commonly used sliding window approach. The proposed system is tested using differential GPS and navigational grade INS field test data obtained from a land vehicle experiment. The results showed that the proposed system is a reliable modeless system and platform independent module that requires no priori knowledge of the navigation equipment utilized. In addition, significant accuracy improvement was achieved during long GPS outages.