Label GM-PHD Filter Based on Threshold Separation Clustering
Label GM-PHD Filter Based on Threshold Separation Clustering
About this item
Full title
Author / Creator
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
Subjects
More information
Scope and Contents
Contents
Gaussian mixture probability hypothesis density (GM-PHD) filtering based on random finite set (RFS) is an effective method to deal with multi-target tracking (MTT). However, the traditional GM-PHD filter cannot form a continuous track in the tracking process, and it is easy to produce a large number of redundant invalid likelihood functions in a de...
Alternative Titles
Full title
Label GM-PHD Filter Based on Threshold Separation Clustering
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_99175340ffb9427ba5876261351edc37
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_99175340ffb9427ba5876261351edc37
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s22010070
