1. A method for predicting future states of a vehicle, comprising the steps of: selecting a model having n states reflecting dynamic features of the vehicle; inputting noisy sensor measurements representing a current state of the vehicle to generate (2n +1) sigma points X i where i=0,. .. 2n, each of the sigma points having n states; performing (2n+1) integrations, each integration includes propagating the n-states of the respective sigma points X i through the non-linear function Y i =f(X i ); and combining the propagated sigma points to generate the predicted future states of the vehicle.