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Robust Discrimination of Human vs. Animal Footsteps Using Seismic Signals

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: N10PC20011
Agency Tracking Number: 0921064
Amount: $99,944.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2009
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
20 New England Business Center
Andover, MA 01810
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Aram Faghfouri
 (978) 689-0003
Business Contact
 Byron Green
Phone: (978) 689-0003
Research Institution

We propose to develop innovative statistical signal processing algorithms that discriminate between human and animal footsteps when
processing seismic signatures acquired by Unattended Ground Sensors (UGS) and UGS constellations. The innovation is to extract and statistically analyze features (e.g., energy, pattern, and spectral properties) of the seismic signatures. Furthermore, to increase
the probability of detection (Pd) and reduce false alarms (Pfa) the algorithms track persistent features and their locations when the
seismic source is within the UGS detection range. In Phase I, PSI will develop and test the algorithms using available recorded signals. Performance of the algorithms in terms of Pd vs. Pfa will be investigated by adding noise and anomalous vibrations to the signal. We expect Pd exceeding 0.9 with Pfa below 0.01 for high signal-to-noise ratios (SNR), and Pd exceeding 0.75 with Pfa below 0.05 for low SNR. The capability to discriminate human vs. animal seismic sources in rural areas and borders is expected to benefit the military
(e.g., surveillance, reconnaissance), DHS (e.g., border control), and civil communities (e.g., detection of construction near pipes or cables).

* Information listed above is at the time of submission. *

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