A nonlinear filtering method called Interacting Multiple Region Model (IMRM) is proposed to estimate the state and continuous system parameter together.IMRM regards the continuous system parameter space as a set of disjoint sub-regions

and each sub-region is assigned to a sub-model respectively.IMRM runs a bank of sub-filters in parallel.At each time step

IMRM computes the mixed initial condition for each sub-model by interaction operation

and each sub-filter estimates the state and system parameter on the condition that the system parameter belongs to a unique sub-region.In order to implement the IMRM efficiently

Unscented Transformation based IMRM (UT-IMRM) is developed by using the unscented kalman filter as the sub-filter.A target tracking experiment is designed to test the performance of UT-IMRM.Experimental results show that UT-IMRM achieves better estimation performance than that of IMM when the system parameter doesnt belong to the IMM model set.