A fuzzy adaptive algorithm for maneuvering target based on current statistical model

被引：0

作者：

Liu W.-S. ^{[1
]}

Pan H.-P. ^{[1
]}

Li Y.-A. ^{[2
]}

机构：

[1] School of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, 310018, Zhejiang

[2] School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, 710072, Shaanxi

来源：

Binggong Xuebao/Acta Armamentarii | 2016年 / 37卷 / 11期

关键词：

Current statistical model; Fuzzy adaptive filtering; Jerk model; Maneuvering target; Ordnance science and technology; Strong tracking;

D O I：

10.3969/j.issn.1000-1093.2016.11.011

中图分类号：

学科分类号：

摘要：

A fuzzy adaptive algorithm is proposed for the imperfections of tracking a maneuvering target using conventional algorithm based on current statistical model. Maneuvering frequency is adjusted in real time by fuzzy reasoning according to the normalized residual and its change rate. Acceleration variance is depicted using residual power function, and the mean value of current acceleration is updated by the deviation between the estimated and predicted values of acceleration. On this basis, the weight of proposed algorithm is revised by Gauss membership function and strong tracking algorithm. Fuzzy adaptive algorithm is not restricted by maneuvering frequency given manually and extreme value of maximum acceleration, which is suitable for the different ranges and degrees of maneuvering. The performance of the proposed algorithm is tested by tracking three typical maneuvering targets, such as step maneuvering, circular maneuvering, and Jerk maneuvering. Simulated results show the tracking range is expanded using the proposed algorithm compared with the conventional tracking algorithm based on current model and the adaptive algorithm based on Jerk model. The proposed algorithm has good steady-state and transient characteristics, and its tracking accuracy and convergence rate are superior to those of the other two algorithms. © 2016, Editorial Board of Acta Armamentarii. All right reserved.

引用

页码：2037 / 2043

页数：6

共 24 条

[1]

Li X.R., Jilkov V.P., Survey of maneuvering target tracking. Part I: dynamic models, IEEE Transactions on Aerospace and Electronic Systems, 39, 4, pp. 1334-1364, (2003)

[2]

Tafti A.D., Sadati N., A hybrid fuzzy adaptive tracking algorithm for maneuvering targets, IEEE International Conference on Fuzzy System, pp. 1869-1873, (2008)

[3]

Naidu V., Raol J.R., Performance evaluation of interacting multiple model Kalman filter, IETE Journal of Education, 49, 3, pp. 95-108, (2008)

[4]

Khaloozadeh H., Karsaz A., Modified input estimation technique for tracking maneuvering targets, IET Proceedings-Radar, Sonar and Navigation, 3, 1, pp. 30-41, (2009)

[5]

Bahari M.H., Pariz N., High maneuvering target tracking using an input estimation technique associated with fuzzy forgetting factor, Scientific Research and Essay, 4, 10, pp. 936-945, (2009)

[6]

Yang J.L., Ji H.B., High maneuvering target-tracking based on strong tracking modified input estimation, Scientific Research and Essays, 5, 13, pp. 1683-1689, (2010)

[7]

Challa S., Morelande M.R., Musicki D., Et al., Fundamentals of Object Tracking, (2015)

[8]

Kim H.S., Park J.G., Lee D., Adaptive fuzzy IMM algorithm for uncertain target tracking, International Journal of Control, Automation, and Systems, 7, 6, pp. 1001-1008, (2009)

[9]

Wang X.H., Yang X.Y., Qin Z., Et al., Hierarchical interacting multiple model algorithm based on improved current model, Journal of Systems Engineering and Electronics, 21, 6, pp. 961-967, (2010)

[10]

Mehrotra K., Mahapatra P.R., A Jerk model for tracking highly maneuvering targets, IEEE Transactions on Aerospace and Electronic System, 33, 4, pp. 1094-1105, (1997)

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