Multi-Sensor Multi-Object Tracking with the Generalized Labeled Multi-Bernoulli Filter

Multi-Sensor Multi-Object Tracking with the Generalized Labeled Multi-Bernoulli Filter

This paper proposes an efficient implementation of the multi-sensor generalized labeled multi-Bernoulli (GLMB) filter. Like its single-sensor counterpart, such implementation requires truncating the GLMB sum. However the single-sensor case requires solving 2-D ranked assignment problems whereas the...

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Bibliographic Details
Main Authors: Vo, Ba-Ngu, Vo, Ba Tuong, Beard, Michael
Format: Journal Article
Language:English
Published: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2019
Subjects:
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
State estimation
Filtering
Random finite sets
Multi-dimensional assignment
Gibbs sampling
RANDOM FINITE SETS
DISTRIBUTED FUSION
MONTE-CARLO
LOCALIZATION
Online Access:http://purl.org/au-research/grants/arc/DP170104854
http://hdl.handle.net/20.500.11937/90802

Internet

http://purl.org/au-research/grants/arc/DP170104854
http://hdl.handle.net/20.500.11937/90802

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