Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array
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Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array Dan Li Department of Electrical and Computer Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691, USA Email: [email protected]
Yu Hen Hu Department of Electrical and Computer Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691, USA Email: [email protected] Received 9 January 2002 and in revised form 13 October 2002 A novel sensor network source localization method based on acoustic energy measurements is presented. This method makes use of the characteristics that the acoustic energy decays inversely with respect to the square of distance from the source. By comparing energy readings measured at surrounding acoustic sensors, the source location during that time interval can be accurately estimated as the intersection of multiple hyperspheres. Theoretical bounds on the number of sensors required to yield unique solution are derived. Extensive simulations have been conducted to characterize the performance of this method under various parameter perturbations and noise conditions. Potential advantages of this approach include low intersensor communication requirement, robustness with respect to parameter perturbations and measurement noise, and low-complexity implementation. Keywords and phrases: target localization, source localization, acoustic sensors, collaborative signal processing, energy-based, sensor network.
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INTRODUCTION
Distributed networks of low-cost microsensors with signal processing and wireless communication capabilities have a variety of applications [1, 2]. Examples include under water acoustics, battlefield surveillance, electronic warfare, geophysics, seismic remote sensing, and environmental monitoring. Such sensor networks are often designed to perform tasks such as detection, classification, localization, and tracking of one or more targets in the sensor field. These sensors are typically battery-powered and have limited wireless communication bandwidth. Therefore, efficient collaborative signal processing algorithms that consume less energy for computation and communication are needed. An important collaborative signal processing task is source localization. The objective is to estimate the positions of a moving target within a sensor field that is monitored by a sensor network. This may be accomplished by (a) measuring the acoustic, seismic, or thermal signatures emitted from the source—the moving target, at each sensor node of the network; and then (b) analyzing the collected source signatures collaboratively among different sensor modalities and different sensor nodes. In this paper, our focus will be on collaborative source localization based on acoustic signatures.
Source localization based on acoustic signature has broad applications: in sonar signal processing, the focus is on locating under-water acoustic sources using an array of hydrophones [3, 4]. Microphone arrays have been used to localize and track human speakers in an in
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