Focal plane array nonlinearity and nonuniformity impacts to target detection with thermal infrared imaging spectrometers

Recent studies have demonstrated the potential for spectrally discriminating low contrast ground-based military targets in the thermal infrared for day/night reconnaissance, surveillance, and targeting applications. Although the underlying spectral features have been found to be very subtle in most cases, good detection performance is achievable due to the generally high band-to-band spectral correlation of terrestrial back,grounds. Recently, attempts have been made to develop imaging spectrometers of sufficient quality to preserve this high background spectral correlation and, in the process, provide robust target detection capabilities. One key issue which must be addressed in the sensor design is the impact of focal plane nonlinearity and nonuniformity on spectral correlation. In this paper, we present the details of a Monte-Carlo model which was developed to quantify this impact as a function of focal plane array characteristics for three sensing modalities: a dispersive spectrometer, a temporal Fourier transform spectrometer, and a spatial Fourier transform spectrometer. The results illustrate distinct differences in how these focal plane error sources propagate into the spectral domain and perturb the measured spectral statistics.