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Power-Aware Acoustic Processing

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Information Processing in Sensor Networks (IPSN 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2634))

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Abstract

We investigated tradeoffs between accuracy and battery-energy longevity of acoustic beamforming on disposable sensor nodes subject to varying key parameters: number of microphones, duration of sampling, number of search angles, and CPU clock. Beyond finding the most energy efficient implementation of the beamforming algorithm at a specified accuracy, we enable application-level selection of accuracy based on the energy required to achieve this accuracy. We measured the energy consumed by the HiDRA node, provided by Rockwell Science Center, employing a 133-MHz StrongARM processor. We compared the accuracy and energy of our time-domain beamformer to a Fourier-domain algorithm provided by the Army Research Laboratory (ARL). With statistically identical accuracy, we measured a 300x improvement in energy efficiency of the CPU relative to this baseline. We present other algorithms under development that combine results from multiple nodes to provide more accurate line-of-bearing estimates despite wind and target elevation.

This work was sponsored by the Defense Advanced Research Projects Agency and Air Force Research Laboratory, Air Force Materiel Command, USAF, under agreement number F30602-99-1-0529. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Defense Advanced Research Projects Agency, the Air Force Research Laboratory, or the U.S. Government.

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© 2003 Springer-Verlag Berlin Heidelberg

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Riley, R., Schott, B., Czarnaski, J., Thakkar, S. (2003). Power-Aware Acoustic Processing. In: Zhao, F., Guibas, L. (eds) Information Processing in Sensor Networks. IPSN 2003. Lecture Notes in Computer Science, vol 2634. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36978-3_38

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  • DOI: https://doi.org/10.1007/3-540-36978-3_38

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-02111-7

  • Online ISBN: 978-3-540-36978-3

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