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Proceedings Paper

Seismic and acoustic signal identification algorithms
Author(s): Mark D. Ladd; M. Kathleen Alam; Gerard E. Sleefe; Hung D. Nguyen
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Paper Abstract

This paper will describe an algorithm for detecting and classifying seismic and acoustic signals for unattended ground sensors. The algorithm must be computationally efficient and continuously process a data stream in order to establish whether or not a desired signal has changed state (turned-on or off). The paper will focus on describing a Fourier-based technique that compares the running power spectral density estimate of the data to a predetermined signature in order to determine if the desired signal has changed state. How to establish the signature and the detection thresholds will be discussed as well as the theoretical statistics of the algorithm for the Gaussian noise case with results from simulated data. Actual seismic data results will also be discussed along with techniques used to reduce false alarms due to the inherent nonstationary noise environments found with actual data.

Paper Details

Date Published: 21 July 2000
PDF: 15 pages
Proc. SPIE 4040, Unattended Ground Sensor Technologies and Applications II, (21 July 2000); doi: 10.1117/12.392574
Show Author Affiliations
Mark D. Ladd, Sandia National Labs. (United States)
M. Kathleen Alam, Sandia National Labs. (United States)
Gerard E. Sleefe, Sandia National Labs. (United States)
Hung D. Nguyen, Sandia National Labs. (United States)


Published in SPIE Proceedings Vol. 4040:
Unattended Ground Sensor Technologies and Applications II
Edward M. Carapezza; Todd M. Hintz, Editor(s)

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