An Extended Target Tracking Algorithm Based on Gaussian Surface Fitting

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...

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Veröffentlicht in:Mathematical problems in engineering Jg. 2022; S. 1 - 21
Hauptverfasser: Han, Yulan, Xu, Han, Hu, Gangdun, Han, Chongzhao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi 22.04.2022
John Wiley & Sons, Inc
Schlagworte:
Algorithms
Distribution functions
Kinematics
Mathematical models
Mathematical problems
Noise
Parameterization
Sensors
Spatial distribution
Surveillance
Tracking
ISSN:1024-123X, 1563-5147
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:1024-123X
1563-5147
DOI:10.1155/2022/2246522