跟踪(教育)
算法
高斯分布
集合(抽象数据类型)
可靠性(半导体)
曲面(拓扑)
过程(计算)
计算机科学
功能(生物学)
高斯过程
数学
几何学
心理学
教育学
功率(物理)
物理
量子力学
进化生物学
生物
程序设计语言
操作系统
作者
Yulan Han,Han Xu,HU Gang-dun,Chongzhao Han
摘要
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.
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