Future wireless networks will integrate sensing, learning, and communication to provide new
services beyond communication and to become more resilient. Sensors at the network …

Fusing probabilistic information is a fundamental task in signal and data processing with
relevance to many fields of technology and science. In this work, we investigate the fusion of …

The advances and convergence in sensor technology, information and communication
technology, and intelligent analytics have given rise to the Internet of Things or also known …

We propose a computationally efficient, the first so far, multi-sensor extension of the Poisson
multi-Bernoulli mixture (PMBM) filter that accommodates both centralized and distributed …

This article proposes a solution of distributed multiple resolvable group targets tracking
(DMRGTT) by exploring the labeled multi-Bernoulli (LMB) filter and distributed fusion rules …

This paper addresses the density based multi-sensor cooperative fusion using random finite
set (RFS) type multi-object densities (MODs). Existing fusion methods use scalar weights to …

Pose estimation is a key feasibility issue for autonomous navigation of civilian UAVs. In
response to the poor positioning accuracy caused by unknown noise in the standard …

As a fundamental information fusion approach, the arithmetic average (AA) fusion has
recently been investigated for various random finite set (RFS) filter fusions in the context of …

This paper studies the multitarget tracking problem based on an asynchronous network of
sensors with different sampling rates, where each sensor runs a cardinalized probability …

In this chapter, we provide an overview of cutting-edge approaches and remaining
challenges in multisensor multitarget information fusion based on the random finite set …