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dc.contributor.authorMahler, Ronald
dc.identifier.citationMahler, R. 2016. Tracking correlated, simultaneously evolving target populations.

© 2016 SPIE. Multisensor-multitarget tracking algorithms are typically based on numerous statistical independence assumptions. This paper is the fifth in a series aimed at weakening such assumptions. It addresses the statistics of correlated, simultaneously evolving multitarget populations. The correlation between two multitarget popula-tions is approximately modeled using bivariate i.i.d.c. (independent, identically distributed cluster) distributions. Based on this, a joint tracking filter for such populations is devised, in analogy with the cardinalized probability hypothesis density (CPHD) filter.

dc.titleTracking correlated, simultaneously evolving target populations
dc.typeConference Paper
dcterms.source.titleProceedings of SPIE - The International Society for Optical Engineering
dcterms.source.seriesProceedings of SPIE - The International Society for Optical Engineering
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

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