Game theoretic data association for multi-target tracking with varying number of targets

We investigate a game theoretic data association technique for multi-target tracking (MTT) with varying number of targets. The problem of target state-estimate-to-track data association has been considered. We use the SMC-PHD filter to handle the MTT aspect and obtain target state estimates. We mode...

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Bibliographic Details
Main Authors: Abdullah Daniyan, Yu Gong, Sangarapillai Lambotharan
Format: Default Conference proceeding
Published: 2016
Subjects:
Mechanical engineering not elsewhere classified
Multi-target tracking (MTT)
Data association
Game theory
Correlated-equilibrium
Forgetting factor
Regret matching
Particle filter
Sequential Monte Carlo (SMC)
Probability hypothesis density (PHD) filter
Mechanical Engineering not elsewhere classified
Online Access:https://hdl.handle.net/2134/37347
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