A novel adaptive δ‐generalised labelled multi‐Bernoulli filter for multi‐target tracking with heavy‐tailed noise

A novel adaptive δ‐generalised labelled multi‐Bernoulli filter for multi‐target tracking with heavy‐tailed noise

Abstract Conventional δ‐generalised labelled multi‐Bernoulli filter (δ‐GLMB) cannot deal with the problem of the heavy‐tailed process noise and measurement noise. In order to solve this problem, an adaptive δ‐GLMB approach based on minimising Kullback‐Leibler Divergence (KLD) is proposed in this stu...

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Bibliographic Details
Main Authors: Peng Gu, Zhongliang Jing, Liangbin Wu
Format: Article
Language:English
Published: Wiley 2023-03-01
Series:IET Radar, Sonar & Navigation
Subjects:
δ‐GLMB
fixed iteration
inverse Wishart
KLD
student‐t
Online Access:https://doi.org/10.1049/rsn2.12351

Internet

https://doi.org/10.1049/rsn2.12351

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