Browse Publications Technical Papers 2004-01-0752

Neural Network Based Data Fusion for Vehicle Positioning in Land Navigation System 2004-01-0752

Land navigation systems need a precise and continuous position in order to function properly. The sensors commonly found in those systems are differential odometer, global positioning system and 2 or 3 axis inertial measurement unit respectively. Two or more of these complementary positioning methods must be integrated together to achieve the required performance at low cost. The integration, which implies the fusion of noisy data provided by each sensor, must be performed in some optimal manner. Most positioning system designers choose the Kalman filter as the data fusion method. An interesting alternative to the Kalman filter is the artificial neural network (ANN). This paper describes the research conducted to evaluate the potential of an ANN as a centralized fusion method and as nonlinear filters for land vehicle positioning.


Subscribers can view annotate, and download all of SAE's content. Learn More »


Members save up to 43% off list price.
Login to see discount.
Special Offer: With TechSelect, you decide what SAE Technical Papers you need, when you need them, and how much you want to pay.