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A new direction for the US Army Night Vision and Electronic Sensors Directorate is the development of ultra-narrow field of view (UNFOV) infrared target acquisition (TA) systems. Frequently, the performance of these systems is limited by atmospheric turbulence in the imaging path. It is desirable to include the effects of atmospheric turbulence blur in infrared TA models. The current TA models are currently linear shift invariant (LSI) systems with component modulation transfer functions (MTFs). The use of additional MTFs, to account for atmospheric turbulence, requires that the turbulence blur have LSI properties. The primary unresolved issue with the treatment of turbulence blur as an MTF is the LSI characteristics of the blur. Significant variation in spatial blur and temporal blur prohibit the use of a single MTF in an LSI target acquisition model. Researchers at Ben-Gurion University (BGU) use a TA model that includes an LSI blur, which is a temporal average of the turbulence blur. The research described here evaluates the BGU-type treatment of atmospheric MTF and determines it reasonable for inclusion in the US Army's TA model. In addition to the spatial characteristics, the temporal variation of the turbulence blur is also described.

Current target acquisition models are for monochrome imagery systems (single detector). The increasing interest in multispectral infrared systems and color daylight imagers highlights the need for models that describe the target acquisition process for color systems (2 or more detectors).This study investigates the detection of simple color targets in a noisy color background. Color targets are varied separately either in hue or saturation. Noise is created with a mixture ofrandom hue and saturation combinations. Our preliminary result showed a simple two-color (yellow-blue) representation did not improve the standard black-and-white Minimum Resolvable Temperature Difference sensitivity. Subsequent psychophysical experiments reveal that human hue and saturation discriminations interact (the Abney effect) and need to be separated in color target detection modeling. Research is continuing to better define the mathematical relationship between the target acquisition parameters (e.g., temperature difference or intensity contrast) and the color space of hue and saturation.

In this research we show that the target-acquisition performance of an undersampled imager improves with sensor or target motion. We provide an experiment designed to evaluate the improvement in observer performance as a function of target motion rate in the video. We created the target motion by mounting a thermal imager on a precision two-axis gimbal and varying the sensor motion rate from 0.25 to 1 instantaneous field of view per frame. A midwave thermal imager was used to permit short integration times and remove the effects of motion blur. It is shown that the human visual system performs a superresolution reconstruction that mitigates some aliasing and provides a higher (than static imagery) effective resolution. This process appears to be relatively independent of motion velocity. The results suggest that the benefits of superresolution reconstruction techniques as applied to imaging systems with motion may be limited.

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.

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The new emphasis on Anti-Terrorism and Force Protection (AT/FP), for both shore and sea platform protection, has resulted in a need for infrared imager design and evaluation tools that demonstrate field performance against U.S. Navy AT/FP requirements. In the design of infrared imaging systems for target acquisition, a discrimination criterion is required for successful sensor realization. It characterizes the difficulty of the task being performed by the observer and varies for different target sets. This criterion is used in both assessment of existing infrared sensor and in the design of new conceptual sensors. We collected 12 small craft signatures (military and civilian) in the visible band during the day and the long-wave and midwave infrared spectra in both the day and the night environments. These signatures were processed to determine the targets' characteristic dimension and contrast. They were also processed to band limit the signature's spatial information content (simulating longer range), and a perception experiment was performed to determine the task difficulty (N50 and V50). The results are presented and can be used for Navy and Coast Guard imaging infrared sensor design and evaluation.

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