A Robust SMC-PHD Filter for Multi-Target Tracking with Unknown Heavy-Tailed Measurement Noise

In multi-target tracking, the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter is a practical algorithm. Influenced by outliers under unknown heavy-tailed measurement noise, the SMC-PHD filter suffers severe performance degradation. In this paper, a robust SMC-PHD (RSMC-PHD) fi...

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Detalles Bibliográficos
Autores principales: Gong, Yang, Cui, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196810/
https://www.ncbi.nlm.nih.gov/pubmed/34067296
http://dx.doi.org/10.3390/s21113611

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196810/
https://www.ncbi.nlm.nih.gov/pubmed/34067296
http://dx.doi.org/10.3390/s21113611

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