Lattice Smooth Variable Structure Filter for Maneuvering Target Tracking with Model Uncertainty

被引:3
作者
Jiao, Yuzhao [1 ]
Lou, Taishan [1 ]
Zhao, Liangyu [2 ]
Zhao, Hongmei [1 ]
Lu, Yingbo [1 ]
机构
[1] Zhengzhou Univ Light Ind, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
[2] Beijing Inst Technol, Sch Aerosp Engn, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Lattice sampling; Smooth variable structure filter; Optimal smooth boundary layer; Nonlinear uncertainty systems; Maneuvering target tracking; STATE ESTIMATION; KALMAN;
D O I
10.1007/s40998-023-00609-6
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a new lattice smooth variable structure filter (LSVSF) for maneuvering target tracking with model uncertainty. Under the assumption that the probability density function (PDF) is Gaussian-distributed, the nonlinear smooth variable structure filter (SVSF) framework is reconstructed by Bayesian theory. The optimal smooth boundary layer (OSBL) calculation form of the SVSF in a nonlinear framework is proposed. Then, based on lattice sampling methods with low computational complexity, the LSVSF algorithm is obtained. Finally, the LSVSF algorithm is verified on the maneuvering target tracking problem with model uncertainty by three scenarios: uniform motion (UM), coordinated turn (CT) motion and mixed motion (UM and CT). According to the simulation, the proposed LSVSF algorithm has superior tracking accuracy and robustness.
引用
收藏
页码:1689 / 1701
页数:13
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