The use of multiplexers and large focal plane arrays in advanced thermal imaging systems has drawn renewed attention to sampling and aliasing issues in imaging applications. As evidenced by discussions in a recent workshop, there is no clear consensus among experts whether aliasing in sensor designs can be readily tolerated, or must be avoided at all cost. Further, there is no straightforward, analytical method that can answer the question, particularly when considering image interpreters as different as humans and autonomous target recognizers (ATR). However, the means exist for investigating sampling and aliasing issues through computer simulation. The U.S. Army Tank-Automotive Command (TACOM) Thermal Image Model (TTIM) provides realistic sensor imagery that can be evaluated by both human observers and TRs. This paper briefly describes the history and current status of TTIM, explains the simulation of FPA sampling effects, presents validation results of the FPA sensor model, and demonstrates the utility of TTIM for investigating sampling effects in imagery.
The potential of infrared polarized signature components for suppressing background clutter and enhancing the detection of dim targets has been investigated. An imaging infrared polarimeter has been built, field experiments have been conducted, and measured results have been compared with theoretical predictions. A description of the measuring instrument, samples of empirical findings, and comparisons with simple theoretical predictions are presented.
The detectability of ground targets in both the visual and thermal infrared spectral regions is dependent on the details of the vehicle's signature and the characteristics of the scene background. Commonly used signature characteristics, such as visual contrast or thermal temperature contrast, are insufficient for use in the sensor and countermeasure systems. This paper discusses the use of an imaging simulation approah to address this difficulty.