The design and implementation of a self-calibrating distributed acoustic sensing platform

  • Authors:

  • Lewis Girod;Martin Lukac;Vlad Trifa;Deborah Estrin

  • Affiliations:

  • Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles

  • Venue:
  • Proceedings of the 4th international conference on Embedded networked sensor systems
  • Year:
  • 2006

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Abstract

We present the design, implementation, and evaluation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems, particularly distributed source localization. Each ENSBox integrates an ARM processor running Linux and supports key facilities required for source localization: a sensor array, wireless network services, time synchronization, and precise self-calibration of array position and orientation. The ENSBox's integrated, high precision self-calibration facility sets it apart from other platforms. This self-calibration is precise enough to support acoustic source localization applications in complex, realistic environments: e.g., 5 cm average 2D position error and 1.5 degree average orientation error over a partially obstructed 80x50 m outdoor area. Further, our integration of array orientation into the position estimation algorithm is a novel extension of traditional multilateration techniques. We present the result of several different test deployments, measuring the performance of the system in urban settings, as well as forested, hilly environments with obstructing foliage and 20-30 m distances between neighboring nodes.