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SIGMA+ Expands Rad-Nuc Sensor Network to Detect Chemical, Biological Threats

Urban city outline with signs for WMD threats
DARPA’s SIGMA+ program seeks to develop highly sensitive detectors and advanced intelligence analytics to detect minute traces of materials used for chemical, biological, radiological, nuclear, and high-yield explosive (CBRNE) weapons. The SIGMA+ CBRNE detection network would be scalable to cover a major metropolitan city and its surrounding region.

Building on SIGMA’s advanced capability to sniff out illicit radioactive and nuclear materials, SIGMA+ program aims to create additional sensors and networks to detect biological, chemical, and explosives threats

Advanced commercially available technologies—such as additive manufacturing (3-D printing), small-scale chemical reactors for pharmaceuticals, and CRISPR gene-manipulation tools—have opened wide access to scientific exploration and discovery. In the hands of terrorists and rogue nation states, however, these capabilities could be misused to concoct chemical, biological, radiological, nuclear, and high-yield explosive (CBRNE) weapons of mass destruction (WMD) in small quantities and in form factors that are hard to detect.

To meet this challenge DARPA today announced its SIGMA+ program, an expansion of the existing SIGMA program, which detects radiological and nuclear materials. SIGMA+ seeks to develop new sensors and networks that alert authorities to chemical, biological, and explosives threats as well.

“The goal of SIGMA+ is to develop and demonstrate a real-time, persistent CBRNE early detection system by leveraging advances in sensing, data fusion, analytics, and social and behavioral modeling to address a spectrum of threats,” said Vincent Tang, SIGMA+ program manager in DARPA’s Defense Sciences Office (DSO). “To achieve this, we’ve pulled together a team of DARPA program managers who bring expertise in chemistry, biology, data analytics, and social science to address the broad and complex CBRNE space.”

The program calls for the development of highly sensitive detectors and advanced intelligence analytics to detect minute traces of various substances related to WMD threats. SIGMA+ will use a common network infrastructure and mobile sensing strategy, a concept that was proven effective in the SIGMA program. The SIGMA+ CBRNE detection network would be scalable to cover a major metropolitan city and its surrounding region.

To uncover chemical and explosives threats, SIGMA+ seeks unprecedented long-range detection of hundreds of chemicals at trace levels to help authorities identify bomb-making safe houses in large urban areas, for example. Successfully developing scalable, long-range chemical sensors would help enable interdiction of improvised chemical and explosive threats or their constituent materials before an attack occurs.

To quickly alert officials of a biological terror attack, such as the release of anthrax, smallpox or plague viruses, SIGMA+ seeks sensors that can detect, in real time, traces of a wide range of pathogens. The program aims to provide immediate, continuous monitoring of pathogen background levels and spikes, which could indicate malicious release of a biological agent.

New environmental, as well as biomechanical and biochemical sensing methods for detecting threats could provide system sensitivity 10 times greater than the state-of-the-art, which would enable detection of a wider range of biological attacks days earlier, maximizing the effectiveness of countermeasures and prophylaxis. For natural pandemics, SIGMA+ sensing methods could yield awareness of major outbreaks weeks sooner than currently is possible.

The program is structured around two Phases with two planned Broad Agency Announcement (BAA) solicitations. The first phase focuses on developing novel sensors for chemicals, explosives, and biological agents. The Phase 1 sensors BAA is expected to be released on FedBizOpps in March. The second phase focuses on network development, analytics, and integration. The Phase 2 BAA is expected to be released in late 2018.

“If successful, SIGMA+ will demonstrate that automated, distributed networks of sensors, combined with automated intelligence analytics and insights from social science, can be deployed and practically scaled to significantly increase the probability of interdicting CBRNE WMD attacks,” said Tang.

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