Stochastic Path Prediction using the Unscented Transform with Numerical Integration
Derek S. Caveney · 2007
This paper illustrates that the combination of the unscented transform and numerical integration can provide significantly more accurate stochastic predictions of the future state of a nonlinear system for potentially less computation time than similar Kalman-like routines. Within the context of this paper, this improvement is shown in the vehicular path prediction environment, where computation power and memory are kept at an affordable level.