For many real-world systems, which exhibit complex, nonlinear, and hybrid behavior, it is important to accurately track and monitor the state and health of these systems. The continuous state estimation problem has been well studied, and a number of extensions of the Kalman filter to nonlinear systems have been proposed. Hy- brid state estimation poses an additional challenge, because the model must be quickly updated during a mode change to facilitate accurate, real time tracking.