OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): General Warfighting Requirements (GWR); Emerging Threat Requirements The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: Collateral effects predictions are a major consideration for decision-makers when planning counter weapons of mass destruction (C-WMD) operations as unintentional releases of WMD materials can harm non-combatants and have significant strategic implications. In order to study the effectiveness of C-WMD technologies and tactics, researchers use standoff, ground-based long wave infrared (LWIR) hyperspectral imaging (HSI) to quantify the vapor mass of specific chemicals in plumes resulting from explosive-driven test events. The vapor mass quantification measurements are particularly sensitive to the difference in temperature between the plume and the background, which could include some combination of bare-earth, vegetation, blue-sky, and/or clouds. The objective of this topic is to develop a method for calibrating HSI systems for vapor mass quantification of plumes with different backgrounds to increase measurement accuracy and provide estimates of measurement uncertainty. DESCRIPTION: The use of LWIR HSI for standoff vapor mass quantification of plumes has proven very useful for evaluating the ability of C-WMD technologies and tactics to minimize unintentional chemical releases and the associated collateral effects. Thorough field calibration of these systems, including the ability to adjust measurements for different environmental and background conditions, has proven difficult. The near term simulant of interest is Diisopropyl methylphosphonate (DIMP), which is generally disseminated as a fine aerosol and must evaporate before HSI vapor mass measurements can occur. At the same time the fringes of the plume are diffusing and dropping below the HSI pixel detection threshold. This means we will always have less than 100% recovery for an artificial plume with a known mass. A system or method enabling the quantification of HSI capabilities as a function of both chemical mass and thermal background is desired. Required vapor masses range from 10s of grams to 10s of kilograms, and the absolute differential between ambient and background thermal backgrounds in the LWIR range from 1 C to 15 C. To-date, artificially generated plumes from a ground-based disseminator have provided limited calibration data, however, the system relied on evaporation of fine aerosols, requiring long spray durations to achieve desired vapor masses and total mass quantification was limited by environmental diffusion effects. Further, the ground-based dissemination system was limited to highly variable thermal backgrounds, e.g., mix of background terrain, horizon, and sky background, and therefore unable to develop calibration curves as a function of thermal background conditions. Development of an unmanned-aerial-system (UAS) disseminator to release an in-scene reference plume with known vapor mass and sky background would overcome some of the limitations of the ground-based system. Other approaches are also of interest and encouraged for this solicitation. PHASE I: Demonstrate concepts to calibrate an HSI system by generating well-characterized in-scene reference plumes or other calibration targets. Demonstrate that the system could be used to study the effects of different backgrounds, plume heights, and/or temperature differentials. A plan should also be submitted outlining the approach for scaling the system to meet Phase II requirements. PHASE II: Demonstrate the ability of the system to perform HSI calibration and account for the parameters of interest. Systems that generate in-scene reference plumes should be capable of using DIMP or other common simulant materials. All data collected during the demonstration and analysis of the system will be included in the final report along with a user's manual and a data package on all critical system components. Hardware developed will also be delivered to the government. PHASE III DUAL USE APPLICATIONS: Phase III will demonstrate and deliver a complete HSI calibration system capable of accounting for all the parameters of interest. Commercialization strategies will depend heavily on the approach chosen but at a minimum will include sales of systems/services to scientific and commercial users of HSI. REFERENCES: 1. Gallagher, Neal & Wise, Barry & Sheen, David. (2003). Estimation of trace vapor concentration-pathlength in plumes for remote sensing applications from hyperspectral images. Analytica Chimica Acta. 490. 139-152. 10.1016/S0003-2670(03)00177-6. 2. Gallagher, Neal & Wise, Barry & Sheen, David. (2003). Error Analysis for Estimation of Trace Vapor Concentration Pathlength in Stack Plumes. Applied spectroscopy. 57. 614-21. 10.1366/000370203322005283. 3. Hall, Jeffrey & Boucher, Richard & Buckland, Kerry & Gutierrez, David & Keim, Eric & Tratt, David & Warren, David. (2016). Mako airborne thermal infrared imaging spectrometer: performance update. Proc. SPIE 9976, Imaging Spectrometry XXI, 997604. 4. Ifarraguerri, Agustin & Ben-David, Avishai. (2008). Impact of atmospheric boundary layer turbulent temperature fluctuations on remote detection of vapors by passive infrared spectroscopy. Optics express. 16. 17366-82. 10.1364/OE.16.017366. 5. Sheen, David & Gallagher, Neal & Sharpe, Steven & Anderson, Kevin & Schultz, John & Shen, Sylvia & Lewis, Paul. (2003). Impact of background and atmospheric variability on infrared hyperspectral chemical detection sensitivity. Proceedings of SPIE - The International Society for Optical Engineering. 5093. 10.1117/12.488931. 6. Young, S.J.. (2023). Detection and Quantification of Gases in Industrial-stack Plumes Using Thermal Infrared Hyperspectral Imaging. KEYWORDS: Sensor; modeling; plume; UAS; dispersion; CBRN; weapons; simulant
