Context-Aided Sensor Fusion for Enhanced Urban Navigation

Sensors

Enrique David Martí²  David Martín¹  Jesús Garc໚²  Arturo de la Escalera¹  José Manuel Molina² 

[1] Intelligent Systems Lab, Universidad Carlos III de Madrid, Avda de la Universidad 30, 28911 Leganes, Spain; E-Mails:;Applied Artificial Intelligence Group, Universidad Carlos III de Madrid, Avda de la Universidad Carlos III 22, 28270 Colmenarejo, Spain; E-Mails:

关键词: autonomous navigation;    multi-sensor fusion;    intelligent systems;    context exploitation;    urban navigation;   

DOI  :  10.3390/s121216802

来源: mdpi

【 摘 要 】

The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland