Title :
Data Fusion in Space Surveillance: Physics, Modeling, Tracking & Classification
Author_Institution :
Defence & Commun. Syst., EADS, Ulm
Abstract :
Data fusion for the surveillance of space objects is distinguished through the complicated physical environment. The dynamics depends on the phase of the object, like boost, coasting, stationary orbit, or reentry. Sequential Monte Carlo methods are addressed to the tracking and classification problem of space objects within those phases
Keywords :
Monte Carlo methods; astronomical techniques; astronomy computing; sensor fusion; surveillance; tracking; data fusion; endo-atmospheric phase; modern filter methods; reentry vehicle; sequential Monte Carlo methods; space objects classification problem; space objects tracking; space surveillance; Aerodynamics; Aerospace control; Atmospheric modeling; Gravity; Physics; Radar tracking; Sensor fusion; Surveillance; Vehicle dynamics; Vehicles;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 2006 IEEE International Conference on
Conference_Location :
Heidelberg
Print_ISBN :
1-4244-0566-1
Electronic_ISBN :
1-4244-0567-X
DOI :
10.1109/MFI.2006.265659
