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Awards

Topic Information Award/Contract Number Proposal Information Company Performance
Period
Award/Contract
Value
Abstract

H-SB09.2-001
Mobile General Aviation (GA) Aircraft Screener

N10PC20005 0921026
(FY09.2 Phase I)
Use of X-ray Backscatter Imaging to Screen General Aviation Aircraft

American Science and Engineering, Inc.
829 Middlesex Turnpike
Billerica, MA 01821-3907

11/01/2009
to
05/15/2010
$99,837.00

This program will evaluate the effectiveness and application of an appropriately-configured X-ray Backscatter imager to the screening of general aviation aircraft. It builds on work already in progress at AS&E to miniaturize and improve the resolution of single-sided X-ray Backscatter systems.

H-SB09.2-002
Human-Animal Discrimination Capability for Unattended Ground Sensors

N10PC20011 0921064
(FY09.2 Phase I)
Robust Discrimination of Human vs. Animal Footsteps Using Seismic Signals (7279-560)

Physical Sciences Inc.
20 New England Business Center
Andover, MA 01810-1077

11/01/2009
to
05/15/2010
$99,944.00

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).

H-SB09.2-002
Human-Animal Discrimination Capability for Unattended Ground Sensors

N10PC20010 0921145
(FY09.2 Phase I)
Diamondback: Sensor Fusion and Feature-Based Human/Animal Classification for UGS

Scientific Systems Company, Inc.
500 West Cummings Park, Suite 3000
Woburn, MA 01801-6562

11/01/2009
to
05/15/2010
$99,976.69

Unattended ground sensors (UGS) are essential in order to determine if personnel are illegally walking across a border for homeland security . However, a problem with current UGS units and their implementation is that they are poor at discriminating between humans and animals. The main reason for this is that the signal processing algorithms for classification are currently limited to using cadence differences between humans and animals. Such an approach can be defeated by the adversary if they mimic such movement. False alarms set off by the UGS units increases the workload of US Customs and Border Patrol (CBP) agents unduly. New signal processing algorithms that generate fewer false alarms are possible if they utilize other feature vectors in the seismic data beyond cadence Typical UGS units include seismic, acoustic and infra red sensors. A multimodal approach that uses acoustic and infra red sensors along with the seismic sensor is likely to further reduce the false alarm rate. Scientific Systems Company Inc. (SSCI) is teaming with Crane Wireless Monitoring Solutions (Crane) for this project. SSCI has extensive experience with signal processing and pattern recognition techniques and Crane has significant experience in developing UGS systems and intrusion detection algorithms.