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

D11PC20001 0922010
(FY09.2 Phase II)
AS&E Phase II Aircraft Scanner

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

12/10/2010
to
03/09/2012
$750,000.00

In this Phase II effort, American Science & Engineering, Inc. (AS&E) will design, fabricate, test and deliver a mobile X-ray Backscatter one-sided imaging system suitable for examining general aviation aircraft for the presence of weapons, contraband or other proscribed items. The system employs a high resolution X-ray Backscatter imaging module mounted on an omni-directional host platform, providing exceptional motion control and versatility for imaging key points on general aviation aircraft, including engines, wings, fuselage, and empennage. The system incorporates collision avoidance to prevent any inadvertent contact with the object being scanned. Real time imagery is displayed to the operator, who controls the system from a co-located graphical user interface. The operator can manipulate and analyze the resulting images using the included software toolkit. The aircraft scanner can be easily moved from location to location within the airport using its own power, or it can be loaded onto a standard flatbed transport for more distant relocations. The system is safe for the operator, the item scanned and the surrounding area. A prototype system, training, manuals and support will be provided within the twelve month program.

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.

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

D11PC20039 0922002
(FY09.2 Phase II)
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

11/14/2010
to
11/13/2012
$749,999.00

The Department of Homeland Security (DHS) needs a low cost reliable automated system to detect illegal border crossings. Current seismic UGS systems use cadence-based intrusion detection algorithms and are easily confused between humans and animals. The ensuing false alarms reduce the trustworthiness of the system and lead to unnecessary actions which may be costly. Scientific Systems Company Inc. (SSCI) through its Phase I research has developed and tested novel signal processing and classification algorithms to robustly discriminate between humans, animals and vehicles. SSCI identified that foot contact characteristics have a significant impact on the time-frequency characterization of recorded seismic signals. SCCI is teaming with Crane Wireless Systems (Crane WMS) and Applied Research Associates (ARA) for the Phase II work. SSCI will provide the signal processing and classification expertise, and Crane Wireless Monitoring Solutions and Applied Research Associates, both leading provides of Seismic Unattended Ground Sensors, will provide the hardware platform and systems support for porting the classification algorithms onto the UGS sensors. The UGS sensors will be field tested with input from the DHS for performance evaluation. SSCI intends to transition and commercialize the UGS technology using licensing arrangements for the signal processing, classification and power management algorithms.