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Passive millimeter wave (pmmW) imagers are quickly becoming practical sensor candidates for military and nonmilitary tasks. Our focus was to adapt the Night Vision [U.S. Army Research Development and Engineering Command, Communications and Electronics Research Development and Engineering Center, Night Vision and Electronics Sensors Directorate (NVESD)] passive thermal infrared imager performance models and apply them to pmmW imaging systems for prediction of field performance for the task of small watercraft and boat identification. The Night Vision Lab's infrared sensor model has been evolving since the 1950s, with the most current model being NVThermIP [Night Vision Thermal and Image Processing (NVThermIP) Model Users Manual, Rev. 9 (U.S. Army RDECON, CERDEC, NVESD, 2006)]. It has wide recognition as an engineering tool for sensor evaluation. This effort included collecting pmmW signatures for a representative set of targets, conducting an observer perception experiment, and deriving the task difficulty criteria that can be used in NVThermIP for identification of boats. The task difficulty criteria are used by designers and managers to create systems capable of meeting specific performance criteria in the field. [c] 2010 Optical Society of America OCIS codes: 040.6808, 040.2235, 110.6820, 110.6795.

In the last half-decade, the extended shortwave infrared (eSWIR) atmospheric band has become a focus of investigation for its potential to provide better object discrimination at range than the visible, as well as the near, shortwave, midwave, and longwave infrared bands, particularly in degraded visual environments such as smoke, dust, and smog. However, any detection band is only as useful as the best available detector, and thus, an investigation into the design of detectors for use in the eSWIR band is necessary before standards are established and applications put into practice. We examine the relationship between detector parameters and targeting performance in the eSWIR band for both passive and active detection. The effects of pixel pitch, dark current, read noise, frame rate, quantum efficiency, and well depth are examined and ranked in importance to an eSWIR system's performance. [ABSTRACT FROM AUTHOR]