Hybrid system is a complex system exhibits hybrid behavior comprising of continuous states and discrete mode of operation. Interaction of continuous state and discrete modes makes the non-linear plant dynamics a complex. Online monitoring of states and discrete modes of operation is a difficult task where the dynamics of the system is corrupted by state and measurement noise with parametric uncertainty. Applications such as fault tolerant control, adaptive control, and fault detection and identification (FDI) depend on the simultaneous estimation of the hybrid system’s state and parameters. An estimating scheme for the state and parameters of a non-linear switching hybrid dynamic system has been provided simultaneously by the authors in this study. A hybrid system with continuous states and discrete modes of dynamics has had its state and parameter estimated using joint and dual state and parameter estimation techniques. For the simultaneous estimate of the state and parameter of the hybrid system, the joint unscented Kalman filter (JUKF) and the dual unscented Kalman filter (DUKF) are compared. Computer experiments were conducted to evaluate the estimate scheme’s performance on a benchmark example. The findings obtained indicate that the dual unscented Kalman filter based estimation scheme is the most appropriate option for state and parameter estimation.