Trajectory PHD Filter for Adaptive Measurement Noise Covariance Based on Variational Bayesian Approximation

In order to solve the problem that the measurement noise covariance may be unknown or change with time in actual multi-target tracking, this paper brings the variational Bayesian approximation method into the trajectory probability hypothesis density (TPHD) filter and proposes a variational Bayesian...

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Autores principales:	Xingchen Lu, Dahai Jing, Defu Jiang, Yiyue Gao, Jialin Yang, Yao Li, Wendong Li, Jin Tao, Ming Liu
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2022-06-01
Colección:	Applied Sciences
Materias:	trajectory PHD filter variational Bayesian approximation noise covariance matrix inverse Gamma distribution estimation of trajectory
Acceso en línea:	https://www.mdpi.com/2076-3417/12/13/6388
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