Abstract

This paper addresses the problem of distributed target tracking, performed by a network of agents which update their local estimates asynchronously. The proposed solution extends and improves an existing consensus-based distributed target tracking framework to cope with real-world settings in which each agent is driven by a different clock. In the consensus-based target tracking framework, it is assumed that only a few agents can actually measure the target state at a given time, whereas the remainder is able to perform a model-based prediction. Subsequently, an algorithm based on max-consensus makes all the agents agree, in finite time, on the best available estimate in the network. The limitations imposed by the assumption of synchronous updates of the network nodes are here overcome by the introduction of the concept of asynchronous iteration. Moreover, an event-based approach makes for the lack of a common time scale at the network level. Furthermore, the synchronous scenario can be derived as a special case of the asynchronous setting. Finally, numerical simulations confirm the validity of the approach. © 2013 IEEE.

Autore Pugliese

• Petitti Antonio

Tutti gli autori

• Giannini S.; Petitti A.; Di Paola D.; Rizzo A.

Titolo volume/Rivista

Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes

Anno di pubblicazione

2013

ISSN

0191-2216

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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