DocumentCode
1808054
Title
Multi-Bernoulli filter for superpositional sensors
Author
Nannuru, Santosh ; Coates, Mark
Author_Institution
Electr. & Comput. Eng. Dept., McGill Univ., Montreal, QC, Canada
fYear
2013
fDate
9-12 July 2013
Firstpage
1632
Lastpage
1637
Abstract
The superpositional sensor model encompasses an important class of sensors such as acoustic sensors and radio-frequency sensors used for multi-target tracking. Recently, random finite set based moment filters such as PHD and CPHD filters have been developed for superpositional sensors. In this paper we derive multi-Bernoulli filter equations for superpositional sensors. The multi-Bernoulli update is derived by defining a conditional PHD for each component of the multi-Bernoulli random finite set and then following an approach similar to that used in deriving the CPHD filter update equation for superpositional sensors. The cardinality distribution is also updated along with the conditional PHD.
Keywords
filtering theory; sensors; CPHD filters; acoustic sensors; cardinality distribution; conditional PHD; multiBernoulli filter equations; multiBernoulli random finite set; multitarget tracking; radiofrequency sensors; random finite set based moment filters; superpositional sensor model; Covariance matrices; Equations; Mathematical model; Sensor fusion; Target tracking; CPHD filter; PHD filter; multi-Bernoulli filter; multi-target tracking; random finite set; superpositional sensors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location
Istanbul
Print_ISBN
978-605-86311-1-3
Type
conf
Filename
6641196
Link To Document