Authors:
Samuel B. Lazarus
1
;
Antonios Tsourdos
1
;
João Sequeira
2
and
Al Savvaris
1
Affiliations:
1
Cranfield University, United Kingdom
;
2
Instituto Superior Técnico, Portugal
Keyword(s):
Multiple Sensor Fusion, Data Fusion, EKF based Navigation, Interval Analysis (IA), Robust Navigation, Covariance Intersection (CI), Maximum Likelihood (ML), Orthogonal Gnanadesikan-Kettenring (OGK).
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Information-Based Models for Control
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
;
Surveillance
;
Vehicle Control Applications
Abstract:
This paper addresses the comparison of robust estimation of a covariance matrix in vehicle navigation task to express the uncertainty when fusing information from multiple sensors. The EKF estimates are fused with the Interval Analysis estimates and further the results are fused using the Covariance Intersection (CI), Maximum Likelihood (ML) and a class of Orthogonal Gnanadesikan-Kettenring (OGK) estimators. The simulation results presented show that the variation between CI and OGK and the correlation between sensors are significant in the presence of outliers.