Algorithm and system advancements to enable infrared standoff trace detection

Abstract

Current commercially fielded approaches for detection of trace materials (explosives, narcotics, low volatility chemical warfare agents and other hazardous chemicals) on surfaces require physical collection and analysis of the trace material. Although these techniques are very sensitive, they require unseen particles to be collected from the surface of the substrate being screened and be transferred to the analysis system. This collection process requires human input (and close-proximity exposure to the screened article, which could pose a safety threat), introduces a fundamental limit on the screening speed, and limits the types of surfaces that can be successfully tested for trace materials to those with good “wipe-ability”. The Intelligence Advanced Research Projects Activity (IARPA) SILMARILS program has demonstrated the capability to detect trace explosives at levels comparable with Explosive Trace Detection (ETD) systems, and narcotics at similar levels. This paper details the algorithms and sensor advances that have enabled these results. A number of relevant experimental test campaigns are discussed including: detection of target chemicals on harvested “real world” substrates such as wood, auto tires, smooth and rough metal, plastics, vinyl, leather, various fabrics, and pig skin (comparable to human skin with respect to fat, water, and hemoglobin content); detection of traces of explosives on portable electronic devices (including after cleaning with organic solvents); and field testing at the 2019 Indianapolis 500 race, where incoming spectator vehicles were screened for explosives simulants (with blind positive controls provided by test and evaluation team rental cars).