Estimation of target location via likelihood approximation in sensor networks

Authors:
Paolo Addesso;Stefano Marano;Vincenzo Matta
Affiliations:
Department of Information and Electrical Engineering, University of Salerno, Fisciano, SA, Italy;Department of Information and Electrical Engineering, University of Salerno, Fisciano, SA, Italy;Department of Information and Electrical Engineering, University of Salerno, Fisciano, SA, Italy
Venue:
IEEE Transactions on Signal Processing
Year:
2010

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Abstract

A fully decentralized sensor network, without fusion center, is deployed to estimate the position of a target. Taking advantage of the limited communication range of the nodes, and exploiting their (unknown) location inside the surveyed area, the likelihood profile is approximately reconstructed. A distributed ML-like estimator is, therefore, proposed and its asymptotic performance is investigated analytically, while computer experiments assess the behavior of the estimator in nonasymptotic regimes. The differences between one- and two-dimensional scenarios are also discussed.