TY - JOUR 
A1 - Toledo Moreo, Rafael
AU - Colodro Conde, Carlos
AU - Toledo Moreo, Francisco Javier
T1 - A Multiple-Model Particle Filter Fusion Algorithm for GNSS/DR Slide Error Detection and Compensation
Y1 - 2018
SN - 2076-3417
UR - http://hdl.handle.net/10317/7757
AB - Continuous accurate positioning is a key element for the deployment of many advanced driver assistance systems (ADAS) and autonomous vehicle navigation. To achieve the necessary performance, global navigation satellite systems (GNSS) must be combined with other technologies. A common onboard sensor-set that allows keeping the cost low, features the GNSS unit, odometry, and inertial sensors, such as a gyro. Odometry and inertial sensors compensate for GNSS flaws in many situations and, in normal conditions, their errors can be easily characterized, thus making the whole solution not only more accurate but also with more integrity. However, odometers do not behave properly when friction conditions make the tires slide. If not properly considered, the positioning perception will not be sound. This article introduces a hybridization approach that takes into consideration the sliding situations by means of a multiple model particle filter (MMPF). Tests with real datasets show the goodness of the proposal
KW - Arquitectura y Tecnología de Computadoras
KW - Positioning
KW - Navigation
KW - Data fusion
KW - Odometry
KW - Particle filter
KW - Multiple-model filter
KW - 3325 Tecnología de las Telecomunicaciones
LA - eng
PB - MDPI
ER -