Refining Atmosphere Profiles for Aerial Target Detection Models.

Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical "pull-down" conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera's performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.

Detection of small targets in the infrared: an infrared search and track tutorial.

Airborne target detection in the infrared has been classically known as infrared search and track or IRST. From a military point of view, it can be described as target detection at long ranges where the target image is subpixel in size. Here, the target is "unresolved." It can also describe the detection of aircraft near the observer using distributed apertures in a spherical detection field. From a commercial point of view, an important application is drone detection near live airport operations. As drones become more common, the dual-use functionality of IRST systems is expanding. Technology improvements for IRST systems include the wide proliferation of infrared staring focal planes. New readout integrated circuits allow for time-delay-integration of large format detectors. Stare-step sensors in the future appear to be as common as gimbal-scanned thermal imagers. Detection probability analysis and IRST sensor design is different than targeting system design. We provide a tutorial here on IRST system calculations as well as discussions on broadband versus spectral calculations and new technology considerations.

Design considerations for advanced MWIR target acquisition systems.

In this paper, mid-wave infrared (MWIR) sensor optimization is provided as a function of the parameter Fλ/d, where F is the f-number, λ is the effective wavelength, and d is the detector pitch. For diffraction limited systems, acquisition range is related to the instantaneous field of view (detector limited operation) when Fλ/d<1, and to the optical properties (optics limited operation) when Fλ/d>2.0. Range performance is a combination of detector and optics resolution limits when Fλ/d is in between. When the system is not strictly diffraction or sampling limited, the optimal Fλ/d depends on other system component characteristics and conditions. Optical system aberrations affect system resolution and decrease range performance. As background shot noise, dark current shot noise, and read noise increase, range decreases. In the infrared spectral region, atmospheric absorption leads to reemission of thermal energy. The detected reemission creates additional shot noise. Atmospheric attenuation greatly affects MWIR sensor range performance. Next-generation MWIR sensors will have smaller detectors, larger arrays, and better sensitivity to enable Fλ/d-based optimization. Previous studies (ΔT=4K for tracked vehicles) suggest that an initial design point is Fλ/d≈2.0. When detecting low contrast targets (ΔT∼0.1K), sensor gain is used to increase the signal for a desired displayed contrast. This gain increases displayed noise and reduces acquisition range. This is typically not an issue for long-wave infrared sensors due to the excess number of photons in the 8-12 µm band but poses a problem for MWIR sensors, which are photon starved. Under such scenarios, the optimum Fλ/d appears to be about 1.5 for MWIR sensors. The results here provide reasonable strategies for MWIR system optimization and a direction associated with future MWIR focal plane development.