Netted sensors-based vehicle acoustic classification at Tier 1 nodes

Garry M. Jacyna; Carol T. Christou; Bryan George; Burhan F. Necioglu

doi:10.1117/12.607142

27 May 2005 Netted sensors-based vehicle acoustic classification at Tier 1 nodes

Garry M. Jacyna, Carol T. Christou, Bryan George, Burhan F. Necioglu

Proceedings Volume 5796, Unattended Ground Sensor Technologies and Applications VII; (2005) https://doi.org/10.1117/12.607142
Event: Defense and Security, 2005, Orlando, Florida, United States

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.

Citation Download Citation

Garry M. Jacyna, Carol T. Christou, Bryan George, and Burhan F. Necioglu "Netted sensors-based vehicle acoustic classification at Tier 1 nodes", Proc. SPIE 5796, Unattended Ground Sensor Technologies and Applications VII, (27 May 2005); https://doi.org/10.1117/12.607142

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