Conjugate continuous-discrete projection filter via sparse-Grid quadrature

In this article, we study the continuous-discrete projection filter for the exponential-family manifolds with conjugate likehoods. We first derive the local projection error of the prediction step of the continuous-discrete projection filter. We then derive the exact Bayesian update algorithm for a class of discrete measurement processes with additive Gaussian noise. Lastly, we present a numerical simulation of the stochastic van der Pol filtering problem with a nonlinear measurement process. The proposed projection filter shows superior performance compared to several state-of-the-art parametric continuous-discrete filtering methods.