Sigma point methods in optimal smoothing of non-linear stochastic state space models
Simo Särkkä, Jouni Hartikainen · 2010
In this article, we shall show how the sigma-point based approximations that have previously been used in optimal filtering can also be used in optimal smoothing. In particular, we shall consider unscented transformation, Gauss-Hermite quadrature and central differences based optimal smoothers. We briefly present the smoother equations and compare performance of different methods in simulated scenarios.