Continuous-time and continuous–discrete-time unscented Rauch–Tung–Striebel smoothers

This article considers the application of the unscented transformation to approximate fixed-interval optimal smoothing of continuous-time non-linear stochastic dynamic systems. The proposed methodology can be applied to systems, where the dynamics can be modeled with non-linear stochastic differential equations and the noise corrupted measurements are obtained continuously or at discrete times. The smoothing algorithm is based on computing the continuous-time limit of the recently proposed unscented Rauch–Tung–Striebel smoother, which is an approximate optimal smoothing algorithm for discrete-time stochastic dynamic systems.