Original article: A new EP-based α-β-γ-δ filter for target tracking

Authors:
Chun-Mu Wu;Ching-Kao Chang;Tung-Te Chu
Affiliations:
Department of Mechanical Engineering and Automation Engineering, Kao Yuan University, No. 1821, Jhongshan Rd., Lujhu Township, Kaohsiung County, 821, Taiwan, ROC;Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, No. 2, Juoyue Rd., Nantz District, Kaohsiung, 811, Taiwan, ROC;Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, No. 2, Juoyue Rd., Nantz District, Kaohsiung, 811, Taiwan, ROC
Venue:
Mathematics and Computers in Simulation
Year:
2011

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Abstract

This study explores a new fourth-order target-tracking @a-@b-@c-@d filter using an evolutionary programming (EP) for numerical simulation in view that the current third-order @a-@b-@c filter system tracks only the target's position and velocity but not its acceleration. As demonstrated, the new @a-@b-@c-@d filter exhibits a significantly improved tracking accuracy over the conventional @a-@b-@c filter. Not unexpectedly, however, the new @a-@b-@c-@d 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 @a-@b-@c-@d 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 @a-@b-@c-@d filter is compared with those by other filters to illustrate the efficiency of the former filter.