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Optical detection systems play a vital role in the early warning detection of airborne biological agents.
Fluorescence and elastic scattering signals have been historically exploited in order to characterize and profile
bioaerosols and yield information that can help suggest the occurrence of a biological attack. More recently, other
optical methods, including Raman, infrared, and laser-induced breakdown spectroscopy, have shown promise as
candidate bioaerosol detection systems. The selection of an optimal approach involves careful consideration of
advantages and disadvantages among these various alternative optical methods. Key considerations are detection
probability, false alarm rate, time to detect, and sensitivity. These four parameters are interrelated functions of the
nature of the optical signal - characterized by absorption and/or emission cross-section, information content, and signal
measurement system technology limitations.
Evaluation of prototype systems that exploit optical signatures to detect and warn of the presence of biological
aerosols involves a careful, deliberate process of developing a standardized aerosol challenge that mimics the properties
of not only a biological agent release, but also the highly complex natural and anthropogenic aerosol background. The
key to developing a test methodology involves 1) interpretation of the limited background aerosol data, 2) development
of dynamic aerosol challenge capabilities, and 3) integration of experimental design principles in the development and
execution of artificial challenge tests and in the reduction and interpretation of sensor system performance based on the
test results.
Evaluation of prototype systems that exploit optical signatures to detect and warn of the presence of biological aerosols involves a careful, deliberate process of developing a standardized aerosol challenge that mimics the properties of not only a biological agent release, but also the highly complex natural and anthropogenic aerosol background. The key to developing a test methodology involves 1) interpretation of the limited background aerosol data, 2) development of dynamic aerosol challenge capabilities, and 3) integration of experimental design principles in the development and execution of artificial challenge tests and in the reduction and interpretation of sensor system performance based on the test results.
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