activity
20182021
most citedMulti-sensor joint target detection, tracking and classification via Bernoulli filter

1 citations · 2 across the 4 of their papers we have counts for

collaborators

9 papers

eess.SP2021

A Variational Bayes Moving Horizon Estimation Adaptive Filter with Guaranteed Stability

Xiangxiang Dong, Giorgio Battistelli, Luigi Chisci +1

This paper addresses state estimation of linear systems with special attention on unknown process and measurement noise covariances, aiming to enhance estimation accuracy while pre…

eess.SP20211 cited

Multi-sensor joint target detection, tracking and classification via Bernoulli filter

Gaiyou Li, Ping Wei, Giorgio Battistelli +2

This paper focuses on \textit{joint detection, tracking and classification} (JDTC) of a target via multi-sensor fusion. The target can be present or not, can belong to different cl…

eess.SY20211 cited

Principled information fusion for multi-view multi-agent surveillance systems

Bailu Wang, Suqi Li, Giorgio Battistelli +2

A key objective of multi-agent surveillance systems is to monitor a much larger region than the limited field-of-view (FoV) of any individual agent by successfully exploiting coope…

eess.SY2020

Distributed multi-view multi-target tracking based on CPHD filtering

Guchong Li, Giorgio Battistelli, Luigi Chisci +2

This paper addresses distributed multi-target tracking (DMTT) over a network of sensors having different fields-of-view (FoVs). Specifically, a cardinality probability hypothesis d…

cond-mat.stat-mech2020

Generating directed networks with prescribed Laplacian spectra

Sara Nicoletti, Timoteo Carletti, Duccio Fanelli +2

Complex real-world phenomena are often modeled as dynamical systems on networks. In many cases of interest, the spectrum of the underlying graph Laplacian sets the system stability…

eess.SY2019

Fusion of labeled RFS densities with minimum information loss

Lin Gao, Giorgio Battistelli, Luigi Chisci

This paper addresses fusion of labeled random finite set (LRFS) densities according to the criterion of minimum information loss (MIL). The MIL criterion amounts to minimizing the…