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Content Provider | IEEE Xplore Digital Library |
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Author | Xiaohong Sheng Yu-Hen Hu |
Copyright Year | 1991 |
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/spl acute/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. |
Sponsorship | IEEE Signal Processing Society |
Starting Page | 44 |
Ending Page | 53 |
Page Count | 10 |
File Size | 420306 |
File Format | |
ISSN | 1053587X |
Volume Number | 53 |
Issue Number | 1 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-01-01 |
Publisher Place | U.S.A. |
Access Restriction | One Nation One Subscription (ONOS) |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Energy measurement Wireless sensor networks Maximum likelihood estimation Position measurement Acoustic sensors Iterative algorithms Acoustic applications Energy resolution Signal resolution Computational modeling source localization Acoustic energy acoustic intensity maximum likelihood nonlinear least square sensor network |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering |
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