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Distributed, Robust Acoustic Source Localization in a Wireless Sensor Network

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3 Author(s)
Yong Liu ; Coll. of Autom., Northwestern Polytech. Univ., Xi''an, China ; Yu Hen Hu ; Quan Pan

A distributed, robust source location estimation method using acoustic signatures in a wireless sensor network (WSN) is presented. A contaminated Gaussian (CG) noise model is proposed to characterize the impulsive, non-Gaussian nature of acoustic background noise observed in some real-world WSNs. A bi-square M-estimate approach then is applied to provide robust estimation of acoustic source locations in the presence of outlier. Moreover, a Consensus based Distributed Robust Acoustic Source Localization (C-DRASL) algorithm is proposed. With C-DRASL, individual sensor nodes will solve for the bi-square M-estimate of the source location locally using a lightweight Iterative Nonlinear Reweighted Least Square (INRLS) algorithm. These local estimates then will be exchanged among nearest neighboring nodes via one-hop wireless channels. Finally, at each node, a robust consensus algorithm will aggregate the local estimates of neighboring nodes iteratively and converge to a unified global estimate on the source location. The effectiveness and robustness of C-DRASL are clearly demonstrated through extensive simulation results.

Published in:

Signal Processing, IEEE Transactions on  (Volume:60 ,  Issue: 8 )

Date of Publication:

Aug. 2012

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