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Review

Exact Closed-Form Multitarget Bayes Filters

Random Sets LLC, Eagan, MN 55122, USA
Sensors 2019, 19(12), 2818; https://doi.org/10.3390/s19122818
Received: 13 May 2019 / Revised: 3 June 2019 / Accepted: 7 June 2019 / Published: 24 June 2019
(This article belongs to the Section Physical Sensors)
The finite-set statistics (FISST) foundational approach to multitarget tracking and information fusion has inspired work by dozens of research groups in at least 20 nations; and FISST publications have been cited tens of thousands of times. This review paper addresses a recent and cutting-edge aspect of this research: exact closed-form—and, therefore, provably Bayes-optimal—approximations of the multitarget Bayes filter. The five proposed such filters—generalized labeled multi-Bernoulli (GLMB), labeled multi-Bernoulli mixture (LMBM), and three Poisson multi-Bernoulli mixture (PMBM) filter variants—are assessed in depth. This assessment includes a theoretically rigorous, but intuitive, statistical theory of “undetected targets”, and concrete formulas for the posterior undetected-target densities for the “standard” multitarget measurement model. View Full-Text
Keywords: multitarget tracking; random finite set; finite-set statistics; undetected targets multitarget tracking; random finite set; finite-set statistics; undetected targets
MDPI and ACS Style

Mahler, R. Exact Closed-Form Multitarget Bayes Filters. Sensors 2019, 19, 2818. https://doi.org/10.3390/s19122818

AMA Style

Mahler R. Exact Closed-Form Multitarget Bayes Filters. Sensors. 2019; 19(12):2818. https://doi.org/10.3390/s19122818

Chicago/Turabian Style

Mahler, Ronald. 2019. "Exact Closed-Form Multitarget Bayes Filters" Sensors 19, no. 12: 2818. https://doi.org/10.3390/s19122818

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