a new ep-based α–β–γ–δ filter for target tracking

this study explores a new fourth-order target-tracking α–β–γ–δ filter using an evolutionary programming (ep) for numerical simulation in view that the current third-order α–β–γ filter system tracks only the target's position and velocity but not its acceleration. as demonstrated, the new α–β–γ–δ filter exhibits a significantly improved tracking accuracy over the conventional α–β–γ filter. not unexpectedly, however, the new α–β–γ–δ filter takes more computation time in the optimization process. to overcome this weakness, an optimal simulation technique via ep is proposed. the developed ep-based α–β–γ–δ filter finds not only the optimal set of filter parameters to minimize position tracking errors but could also reduce the computation time by up to 95% in some time steps. the trajectory simulated by the ep-based α–β–γ–δ filter is compared with those by other filters to illustrate the efficiency of the former filter.