RT Journal Article
T1 Context-Aided Sensor Fusion for Enhanced Urban Navigation
A1 Marti Muñoz, Enrique David
A1 Martín, David
A1 García, Jesús
A1 Escalera Hueso, Arturo de la
A1 Molina, José M.
A1 Armingol Moreno, José María
AB 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.
PB MDPI
SN 1424-8220
YR 2012
FD 2012-12
LK https://hdl.handle.net/10016/16248
UL https://hdl.handle.net/10016/16248
LA eng
NO This work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485), CICYT TRA2010-20255-C03-01, CICYT TRA2011-29454-C03-02 and mobility grants program of Fundación CajaMadrid
DS e-Archivo
RD 1 jun. 2024