Data Fusion in Space Surveillance: Physics, Modeling, Tracking & Classification
Felix Opitz · 2006
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.