DocumentCode :
1190513
Title :
Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks
Author :
Sheng, Xiaohong ; Hu, Yu-Hen
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA
Volume :
53
Issue :
1
fYear :
2005
Firstpage :
44
Lastpage :
53
Abstract :
A maximum likelihood (ML) acoustic source location estimation method is presented for the application in a wireless ad hoc sensor network. This method uses acoustic signal energy measurements taken at individual sensors of an ad hoc wireless sensor network to estimate the locations of multiple acoustic sources. Compared to the existing acoustic energy based source localization methods, this proposed ML method delivers more accurate results and offers the enhanced capability of multiple source localization. A multiresolution search algorithm and an expectation-maximization (EM) like iterative algorithm are proposed to expedite the computation of source locations. The Crame´r-Rao Bound (CRB) of the ML source location estimate has been derived. The CRB is used to analyze the impacts of sensor placement to the accuracy of location estimates for single target scenario. Extensive simulations have been conducted. It is observed that the proposed ML method consistently outperforms existing acoustic energy based source localization methods. An example applying this method to track military vehicles using real world experiment data also demonstrates the performance advantage of this proposed method over a previously proposed acoustic energy source localization method.
Keywords :
acoustic signal processing; ad hoc networks; iterative methods; maximum likelihood estimation; search problems; wireless sensor networks; Cramer-Rao bound; acoustic signal energy measurement; expectation-maximization; iterative algorithm; maximum likelihood estimation; military vehicles tracking; multiple acoustic sources; multiple-source localization; multiresolution search algorithm; wireless ad hoc sensor network; Acoustic applications; Acoustic sensors; Computational modeling; Energy measurement; Energy resolution; Iterative algorithms; Maximum likelihood estimation; Position measurement; Signal resolution; Wireless sensor networks;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2004.838930
Filename :
1369649
Link To Document :
بازگشت