Probabilistic 2D Acoustic Source Localization Using Direction of Arrivals in Robot Sensor Networks

Wireless Sensor Networks (WSNs) enable susceptible sensing of the environment, offering unprecedented opportunities for observing the physical world. Acoustic source localization is an interesting topic with many possible application areas, such as intruder detection, sniper localization, automatic tracking of speakers and so on. Many existing algorithms are on the premise that the exact coordinates of sensor nodes are already known. In this paper, we propose a vector-based advanced TDoA algorithm that would calibrate the coordinate of the acoustic source by the non-prepositioned nodes. In the meanwhile, the portable sensor nodes would adjust themselves through the feedback of the estimated positions as well. Finally, we show that the proposed mechanism has high accuracy through experiments.

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Acoustic Source Localization in Wireless Sensor Networks

Workshop on Intelligent Information Technology Application (IITA 2007) ◽

10.1109/iita.2007.64 ◽

2007 ◽

Cited By ~ 3

Author(s):

Mingfei Wang ◽

Linlin Ci ◽

Ping Zhang ◽

Yongjun Xu

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Source Localization ◽

Wireless Sensor ◽

Acoustic Source ◽

Acoustic Source Localization

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Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

Journal of Sensors ◽

10.1155/2009/187916 ◽

2009 ◽

Vol 2009 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Neena Imam ◽

Jacob Barhen

Keyword(s):

Sensor Networks ◽

Source Localization ◽

Sensor Arrays ◽

Digital Processing ◽

Acoustic Source ◽

Distributed Sensor Networks ◽

Distributed Sensor ◽

Acoustic Source Localization ◽

Block Algorithms ◽

Processing Platform

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot be readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.

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