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Chiuso, Alessandro and Schenato, Luca (2009) Performance bounds for information fusion strategies in packet-drop networks. [Technical Report] (In pubblicazione)

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Abstract (english)

In this paper we provide some analytical performance bounds for different distributed estimation
schemes for stochastic discrete time linear systems where the communication between the sensors
and the estimation center is subject to random packet loss. In particular, we analyze three
different strategies. The first, named measurement fusion (MF) optimally fuses the raw
measurements received so far from all sensors. The second strategy, named infinite bandwidth filter (IBF), computes the optimal mean square estimator assuming that each node can send all measurements observed up to its current time in a single packet. The last strategy, named open loop partial estimate fusion (OLPEF), simply
sums local state estimates received from each sensor and replace the lost ones with their open
loop counterpart. In particular, we propose novel mathematical tools to derive analytical upper and lower bounds for expected estimation error covariance the MF and the IBF strategies in the scenario of identical sensors and we compare their values with the empirical performance obtained via simulations.

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EPrint type:Technical Report
Anno di Pubblicazione:04 June 2009
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 Automatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Dipartimenti > Dipartimento di Tecnica e Gestione dei Sistemi Industriali
Codice ID:2084
Depositato il:10 Jul 2009 09:29
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