DHS S&T Awards $3.5M for X-ray Technology R&D

Look at that plane taking off at an airport.

The Department of Homeland Security’s (DHS) Science and Technology Directorate (S&T) awarded $3.5 million in research and development funding to improve detection capabilities of X-ray technology used for checked baggage systems at U.S. airports.

“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 S&T. “S&T is making important investments in technology that could be leveraged into the next generation of checked baggage screening equipment.”

The funding, which was awarded under Broad Agency Announcement HSHQDC-17-R-B0003, will be split among three companies, Capture of San Diego, Calif.; DxRay/Rapiscan of Northridge, Calif.; and EV Products of Saxonburg, Penn.

“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.

The original solicitation consisted of three task areas, DHS S&T explained in a statement. The agency is interesting in “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.”

“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).

The winning companies will each focus on different projects, DHS S&T explained:

  • Capture 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 3-D 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 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).”
  • EV Products 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.”

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