An Extended Target Tracking Algorithm Based on Gaussian Surface Fitting. (22nd April 2022)

• Record Type: Journal Article
• Authors: Han, Yulan; Xu, Han; Hu, Gangdun; Han, Chongzhao
• Other Names: Jankowski Łukasz Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2022(2022)
• Publication Date: 2022-04-22
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2022/2246522
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Although the existing algorithms have done a lot of progress in extended target tracking (ETT), most algorithms are limited by the assumption of the target shape, and there are problems with parameter calculations. To solve the problems above, an extended target tracking algorithm based on level set and Gaussian Surface fitting (GSF), is proposed. Different from the existing extended target tracking algorithms, the proposed algorithm uses a level set to implicitly describe the evolution of the estimated shape, eliminates the parameterization process, and uses the GSF to construct the measurement source spatial distribution function (MSSDF) of the extended target. The proposed algorithm can obtain the estimated shape of the extended target without knowing the prior shape and size of the target. The simulation results verify the effectiveness and reliability of the proposed algorithm.