DocumentCode :
1005530
Title :
Distributed Estimation in Large Wireless Sensor Networks via a Locally Optimum Approach
Author :
Marano, Stefano ; Matta, Vincenzo ; Willett, Peter
Author_Institution :
Salerno Univ., Fisciano
Volume :
56
Issue :
2
fYear :
2008
Firstpage :
748
Lastpage :
756
Abstract :
A wireless sensor network (WSN) engaged in a decentralized estimation problem is considered. The nonrandom unknown parameter lies in some small neighborhood of a nominal value and, exploiting this knowledge, a locally optimum estimator (LOE) is introduced. Under the LOE paradigm, the sensors of the network process their observations by means of a suitable nonlinearity (the score function), before delivering data to the fusion center that outputs the final estimate. Usually continuous-valued data cannot be reliably delivered from sensors to the fusion center, and some form of data compression is necessary. Accordingly, we design the scalar quantizers that must be used at the network´s nodes in order to comply with the estimation problem at hand. Such a difficult multiterminal inference problem is shown to be asymptotically equivalent to the already solved problem of designing optimum quantizers for reconstruction (as opposed to inference) purposes.
Keywords :
data compression; sensor fusion; wireless sensor networks; data compression; data fusion; decentralized estimation problem; locally optimum estimator; multiterminal inference problem; wireless sensor network; Bayesian methods; Channel capacity; Data compression; Helium; Joining processes; Maximum likelihood estimation; Parallel architectures; Parameter estimation; Sensor fusion; Wireless sensor networks; Data fusion; distributed estimation; scoring method; wireless sensor networks;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2007.907874
Filename :
4400831
Link To Document :
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