Tracking one dimension state space variables with particle filter method

Particle filter is among the commonly used methods aims tracking of linear and non linear systems. Particle filter takes important place for accurate modeling of nonlinear dynamic systems. Given that the data becomes available instantly, update of the system according to incoming data offers extra gains on better adaptation of instant response and reduces data storage. In this study particle filter investigated on a one dimensional artificial data for the sake of understand theory and working principle.