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Proceedings Paper

Netted sensors-based vehicle acoustic classification at Tier 1 nodes
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Paper Abstract

The MITRE Corporation has embarked on a three-year internally-funded research program in netted sensors with applications to border monitoring, situational awareness in support of combat identification, and urban warfare. The first-year effort emphasized a border monitoring application for dismounted personnel and vehicle surveillance. This paper will focus primarily on the Tier 1 acoustic-based vehicle classification component. We discuss the development and implementation of a robust linear-weighted classifier on a Mica2 Crossbow mote using feature extraction algorithms specifically developed by MITRE for mote-based processing applications. These include a block floating point Fast Fourier Transform (FFT) algorithm and an 8-band proportional bandwidth filter bank. Results of in-field testing are compared and contrasted with theoretically-derived performance bounds.

Paper Details

Date Published: 27 May 2005
PDF: 12 pages
Proc. SPIE 5796, Unattended Ground Sensor Technologies and Applications VII, (27 May 2005); doi: 10.1117/12.607142
Show Author Affiliations
Garry M. Jacyna, The MITRE Corp. (United States)
Carol T. Christou, The MITRE Corp. (United States)
Bryan George, The MITRE Corp. (United States)
Burhan F. Necioglu, The MITRE Corp. (United States)


Published in SPIE Proceedings Vol. 5796:
Unattended Ground Sensor Technologies and Applications VII
Edward M. Carapezza, Editor(s)

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