| Unlike previous generations of thermal imagers, which use scanning detectors sensitive in either the 3-5mum or 8-12mum waveband, advanced or next-generation thermal imagers use two-dimensional (2-D) detector arrays that may be sensitive in more than one waveband. The performance and target acquisition capabilities of earlier-generation thermal imagers are well established and modeled in such programs as FLIR '92, NVTherm, and ACQUIRE1. These performance models guide thermal imager design and acquisition by allowing system designers and purchasers to perform theoretical tradeoff studies between various thermal imagers and to evaluate the impact of new technologies, such as quantum well infrared photodetectors (QWIPs). The introduction of advanced thermal imagers in combination with new operational spaces and scenarios creates new sensor performance modeling challenges. Some of these challenges include accurate prediction of sensor performance resulting from image under-sampling; determination of a suitable representation for mutual information in multi-waveband images; and suitable performance modeling of these sensors in the detection, recognition, and identification of nontraditional targets2. The advanced thermal imager research I report on in this dissertation provides (i) guidance for modeling the operational performance of thermal imaging sensors that produce under-sampled imagery, (ii) a methodology for the collection and assessment of information differences between multi-waveband images, and (iii) a model for thermal imager operational performance prediction in the identification of handheld objects. My research advances thermal imager performance model understanding and provides guidance to system designers in the development of next-generation thermal imagers.; 1 In this document, a "model" is a collection of mathematical formulas that quantitatively characterizes a sensors physical attributes and capabilities. FLIR '92 and NVTherm model the MTF, noise, and sensitivity of thermal imager systems, while ACQUIRE utilizes the results of FLIR '92 and NVTherm to predict system range performance for a specific visual perception task. 2 In this document, traditional targets are military vehicles. All other objects which the target acquisition process is applied are non-traditional targets. |
