DetectionImproving X-ray detection technology

Published 14 September 2018

DHS S&T has awarded a total of nearly $3.5 million in funding to three new research and development (R&D) projects designed to improve the threat detection capabilities of current X-ray technologies for checked baggage systems.

The Department of Homeland Security (DHS) Science and Technology Directorate (S&T) has awarded a total of nearly $3.5 million in funding to three new research and development (R&D) projects designed to improve the threat detection capabilities of current X-ray technologies for checked baggage systems.

“The emergence of homemade explosives has placed many challenges on aviation security screening,” said William N. Bryan, Senior Official Performing the Duties of the DHS Under Secretary for Science and Technology. “S&T is making important investments in technology that could be leveraged into the next generation of checked baggage screening equipment.”

“We are addressing current, ongoing, and upcoming capability gaps with a three-pronged approach utilizing the continuous transition of hardware, software, and knowledge,” said S&T Checked Baggage Program Manager, Sharene Young.

“If successful, these projects will significantly improve operational efficiency and security effectiveness for TSA baggage screening operations,” said Eric Houser, Acting Director of the Analysis and Requirements and Architecture Divisions for the Transportation Security Administration (TSA).

S&T notes that the three project contracts were awarded under Broad Agency Announcement HSHQDC-17-R-B0003, which was issued in December 2016. The solicitation consisted of three task areas: focusing on improving X-ray technologies for bag screening systems, developing advanced algorithm technologies for checked and carry-on baggage, and focusing efforts to refine non-Commercial Off the Shelf long-term device technology.

The following groups and their projects are the funded BAA awards:

·  Capture LLC, of San Diego, CA was awarded $1,168,773 to develop an automated threat detection algorithm for improved detection of prohibited items such as guns and knives. Capture will use a deep learning 3D convolutional neural network approach to enhance algorithm development. The goal is to deploy the automated threat recognition (ATR) algorithm on the TSA’s checkpoint computed tomography (CT) systems. A new ATR will help screening efficiency and will help improve detection of threats.

·  DxRay/Rapiscan, of Northridge, CA was awarded $817,444 to produce 12 large field-of-view, high-output count rate X-ray imaging arrays with high spatial and energy resolution which can operate at room temperature and be manufactured cost effectively. Developing this detector technology will help eliminate false positives in primary screening lanes by adding inline X-ray diffraction (XRD). XRD can resolve false positives, but is time consuming and expensive due to the current need for cryogenically cooled detectors to achieve the required resolution. This new technology directly addresses issues by delivering a better detector with better resolution that can be added in series to existing primary lanes.

·  EV Products, of Saxonburg, PA was awarded $1,498,676 to improve high-speed coded-aperture X-ray scatter imaging (CAXSI) screening to stream-of-commerce rates. The project focuses on high-speed data acquisition and maximizing the count rate through the detector module without compromising other capabilities. This will allow X-ray machines to be more efficient, with both better detection and lower energy needs. Higher efficiency means easier detection of threats with a possibility of increased throughput.

These projects will be managed by the DHS S&T Checked Baggage Program, which supports TSA requirements to improve overall detection and false alarm performance for explosives detection system technologies.

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