In recent years，there have been growing studies in financial area on the dynamics of short-term interest rates，since it is an indispensable tool for interest rate derivatives pricing and risk management． This paper extends the short-rate dynamics from two perspectives: Stochastic volatility and regime switching，respectively． A novel method called particle filter is selected to estimate parameters and unobservable state variables for our Markov switching stochastic volatility model． Then we take our empirical analysis on China’s shortterm inter-bank borrowing interest rate． The results show that the short-rate has both stochastic volatility behavior and regime switching characteristic，and the BS-MSSV model is best for describing the short-rate dynamics． Moreover，our study confirms that neglecting regime switching of volatility mean would lead to overestimating the volatility persistence and worsen the modeling performance．