Performance Analysis for Hybrid State Estimation Problems

Abstract

Hybrid state estimation problems are statistical estimation problems in which both continuous-valued and discrete-valued states and parameters occur. The hybrid state model provides both a natural formulation for many types of surveillance and tracking problems and a powerful framework for deriving theoretically optimal and practical suboptimal tracking algorithms. This report describes research in developing tools for evaluating the performance of optimal hybrid state estimation problems.