Two Measurement Set Partitioning Algorithms for the Extended Target Probability Hypothesis Density Filter

The extended target probability hypothesis density (ET-PHD) filter cannot work well if the density of measurements varies from target to target, which is based on the measurement set partitioning algorithms employing the Mahalanobis distance between measurements. To tackle the problem, two measureme...

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Detalles Bibliográficos
Autores principales: Han, Yulan, Han, Chongzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6630985/
https://www.ncbi.nlm.nih.gov/pubmed/31200450
http://dx.doi.org/10.3390/s19122665

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6630985/
https://www.ncbi.nlm.nih.gov/pubmed/31200450
http://dx.doi.org/10.3390/s19122665

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