NDLI: Distributed multi-sensor fusion using generalised multi-Bernoulli densities

Content Provider	IET Digital Library
Author	Yi, Wei Jiang, Meng Hoseinnezhad, Reza Wang, Bailu
Abstract	A new method for distributed multi-target tracking with multistatic radar systems is presented.The proposed method is based on using generalised covariance intersection (GCI) of multi-object densities for fusion of the posteriors within a multi-object Bayesian filtering scheme. The presented solution is particularly formulated for sensor fusion with posterior densities that are parameterised as generalised multi-Bernoulli (GMB) distributions which are the unlabelled version of VoCVo densities by discarding the labels. To obtain a closed-form solution for fusing GMB densities, the authors use an efficient approximation to the densities. The approximated density is another GMB density that preserves both the first-order moment (intensity or PHD) and the cardinality distribution of the original density. As such, it is called the second-order approximation of the GMB (SO-GMB) density. The resulting explicit expressions for the GCI fusion using SO-GMB approximations allow distributed sensor fusion, not only with VoCVo filters, but also with M-generalised labelled multi-Bernoulli and labelled multi-Bernoulli filters being in place as local filters in the multistatic radar system. In two challenging multi-target tracking scenarios, the tracking performance of the proposed method is shown to outperform the state of art.
Starting Page	434
Ending Page	443
Page Count	10
ISSN	17518784
Volume Number	11
e-ISSN	17518792
Issue Number	Issue 3, Mar (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/11/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2016.0227
Journal	IET Radar, Sonar & Navigation
Publisher Date	2016-09-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximation Theory Cardinality Distribution Distributed Multi-target Tracking Distributed Multisensor Fusion Filtering Method in Signal Processing Filtering Theory First-order Moment Generalised Covariance Intersection Generalised Multi-Bernoulli Densities Generalised MultiBernoulli Distribution Interpolation And Function Approximation Multi-Bernoulli Filter Multi-object Bayesian Filtering Scheme Multistatic Radar System Numerical Analysis Radar Equipment Radar Signal Processing Radar Tracking Second-order Approximation Sensor Fusion SO-GMB Approximation System And Application Target Tracking
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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