Litcius/Paper detail

Event-Triggered Distributed Fusion for Multirate Multisensor Systems With Heavy-Tailed Noises

Ling Zhao, Xinyue Cao, Li Li, Hongjiu Yang

2021IEEE Transactions on Systems Man and Cybernetics Systems20 citationsDOI

Abstract

In this article, event-triggered distributed fusion is investigated for a multirate multisensor system subject to heavy-tailed noises under packet dropout. The heavy-tailed noises are modeled by a multivariate <inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula>-distribution for the multirate multisensor system. An event-triggered local estimator is designed to gain local estimates with packet dropout in communication networks. An event-triggered distributed fusion algorithm is proposed by sequential fast covariance intersection (SFCI) fusion technology. Sufficient conditions on the boundedness of the estimation error scale matrices are given for the event-triggered local estimator and distributed fusion. Finally, numerical simulation is put forward to indicate validity of the presented event-triggered local estimator and distributed fusion.

Topics & Concepts

EstimatorNetwork packetDropout (neural networks)Event (particle physics)Covariance intersectionComputer scienceFusionCovarianceIntersection (aeronautics)Control theory (sociology)AlgorithmReal-time computingMathematicsCovariance matrixArtificial intelligenceStatisticsEngineeringControl (management)Covariance functionMachine learningComputer networkAerospace engineeringQuantum mechanicsLinguisticsPhilosophyPhysicsDistributed Sensor Networks and Detection AlgorithmsTarget Tracking and Data Fusion in Sensor NetworksRadar Systems and Signal Processing