Unknown correlations (UCs) generally exist in a wide spectrum of practical multi-source
information fusion problems, and thereby, their corresponding fusion problems have …

In this study, we provide an overview of recent advances in multisensor multitarget tracking
based on the random finite set (RFS) approach. The fusion that plays a fundamental role in …

Two fundamental approaches to information averaging are based on linear and logarithmic
combination, yielding the arithmetic average (AA) and geometric average (GA) of the fusing …

This paper addresses the problem of distributed multitarget detection and tracking based on
the linear arithmetic average (AA) fusion. We first analyze the conservativeness and Fréchet …

A large-scale multi-object tracker based on the generalised labeled multi-Bernoulli (GLMB)
filter is proposed. The algorithm is capable of tracking a very large, unknown and time …

Networked radar systems have been demonstrated to offer enhanced target tracking
capabilities. An effective radar resource allocation strategy can efficiently optimize system …

The paper addresses the problem of distributed multi-target tracking (MTT) in a network of
sensors having different fields of view (FoVs). Probability hypothesis density (PHD) filters are …

We propose a novel consensus notion, called “partial consensus,” for distributed Gaussian
mixture probability hypothesis density fusion based on a decentralized sensor network, in …

This paper proposes an efficient implementation of the multi-sensor generalized labeled
multi-Bernoulli (GLMB) filter. Like its single-sensor counterpart, such implementation …

This paper considers the problem of the distributed fusion of multiobject posteriors in the
labeled random finite set filtering framework, using a generalized covariance intersection …