A Robust SMC-PHD Filter for Multi-Target Tracking with Unknown Heavy-Tailed Measurement Noise
A Robust SMC-PHD Filter for Multi-Target Tracking with Unknown Heavy-Tailed Measurement Noise
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Full title
Author / Creator
Gong, Yang and Cui, Chen
Publisher
Basel: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Basel: MDPI AG
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Scope and Contents
Contents
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) filter is proposed. In the proposed filter, Student-...
Alternative Titles
Full title
A Robust SMC-PHD Filter for Multi-Target Tracking with Unknown Heavy-Tailed Measurement Noise
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_33a628714b4e4f7aa83f5921329496b3
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_33a628714b4e4f7aa83f5921329496b3
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s21113611
