On comparing statistical and set-based methods in sensor data fusion
Gregory D. Hager, Sofija Engelson, S. Atiya · 2002
The theoretical and practical considerations of two common sensor data fusion methodologies (set based and statistically based parameter estimation) are compared. Their convergence behavior for a variety of simulated problems is examined. Robot localization systems implemented using both methods are described, and their performance is compared. It is concluded that set-based methods have performance that sometimes exceeds that of statistical methods, although this result is highly problem-dependent. These problem dependencies are characterized.>