Technology Gap Analysis for the Detection of Process Signatures Using Less Than Remote Methods

Hartman, John S. ; Atkinson, David A. ; Lind, Michael A. ; Maughan, A. D. ; Kelly, James F.

Pacific Northwest National Laboratory (U.S.)

关键词: Particulates;    Training;    Monitoring;    Remote Sensing;    Sensitivity;   

DOI  :  10.2172/919721
RP-ID  :  PNNL-14988
RP-ID  :  AC05-76RL01830
RP-ID  :  919721

美国|英语

来源: UNT Digital Library

【 摘 要 】

Although remote sensing methods offer advantages for monitoring important illicit process activities, remote and stand-off technologies cannot successfully detect all important processes with the sensitivity and certainty that is desired. The main scope of the program is observables, with a primary focus on chemical signatures. A number of key process signatures elude remote or stand-off detection for a variety of reasons (e.g., heavy particulate emissions that do not propagate far enough for detection at stand-off distances, semi-volatile chemicals that do not tend to vaporize and remain in the environment near the source, etc.). Some of these compounds can provide persistent, process-specific information that is not available through remote techniques; however, the associated measurement technologies have their own set of advantages, disadvantages and technical challenges that may need to be overcome before additional signature data can be effectively and reliably exploited. The main objective of this report is to describe a process to identify high impact technology gaps for important less-than-remote detection applications. The subsequent analysis focuses on the technology development needed to enable exploitation of important process signatures. The evaluation process that was developed involves three interrelated and often conflicting requirements generation activities: • Identification of target signature chemicals with unique intelligence value and their associated attributes as mitigated by environmentally influenced fate and transport effects (i.e., what can you expect to actually find that has intelligence value, where do you need to look for it and what sensitivity and selectivity do you need to see it) • Identification of end-user deployment scenario possibilities and constraints with a focus on alternative detection requirements, timing issues, logistical consideration, and training requirements for a successful measurement • Identification of available measurement technology alternatives and their associated attributes (available off-the-shelf, in near-term development, likely longer-term development and research-phase possibilities). Assembling these requirements into attribute verses generic acceptance criteria level tables and then comparing related attributes between tables allows for rapid visualization of technology gaps and gross estimates of the gap size. By simply weighting the attributes and the requirements in various ways one can also derive the importance of the identified technology gaps. This output can provide the basis for both a near-term technology development roadmap and research focus as well as a decision support tool for selecting the “most likely to succeed” approach. The evaluation process as presented is generally applicable for the determination of measurement technology gaps for a broad range of applications [e.g., nuclear weapons process, chemical weapons production, biological weapons production as well as classical signature categories (e.g., chemical and radionuclide signatures)]. In this paper the method is applied to the specific case of detecting nuclear weapons production processes using semi-volatile chemical signatures as an illustration. This particular case selection allows the leveraging of significant prior knowledge and experience while still being highly relevant to current detection scenario needs.