A probability hypothesis density filter for tracking non‐rigid extended targets using spatiotemporal Gaussian process model

Abstract This paper proposes a random finite set (RFS)‐based algorithm to deal with the tracking problem of multiple non‐rigid extended targets (MNRET) with irregular shapes in the presence of clutter, false alarms and missed detection. The extensions of targets are modelled by spatiotemporal Gaussi...

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Autors principals:	Sunyong Wu, Yusong Zhou, Yun Xie, Qiutiao Xue
Format:	Artigo
Idioma:	Inglês
Publicat:	Wiley 2022-12-01
Col·lecció:	IET Signal Processing
Matèries:	Gaussian mixture non‐rigid extended targets predicted likelihood probability hypothesis density random finite set Spatiotemporal Gaussian process
Accés en línia:	https://doi.org/10.1049/sil2.12158
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