Before revision:  Then the problem of concern is formalized as a task of nonlinear non-Gaussian state filtering under model uncertainty, which is addressed by a dynamic model averaging  based particle filter algorithm . Experimental results show that the proposed solution outperforms remarkably state-of-the-art methods.
After revision:  Then the problem of concern is formalized as a task of nonlinear non-Gaussian state filtering under model uncertainty, which is addressed by a dynamic model averaging (DMA) based particle filter algorithm . Experimental results show that the proposed solution outperforms remarkably state-of-the-art methods.