Proceedings Article | 24 January 2019
Proc. SPIE. 11043, Fifth Conference on Sensors, MEMS, and Electro-Optic Systems
KEYWORDS: Signal to noise ratio, Short wave infrared radiation, Indium gallium arsenide, Sensors, Photons, Electrons, Sensor performance, Modulation transfer functions, Performance modeling, Atmospheric modeling
With the emergence of Shortwave Infrared (SWIR) InGaAs detector arrays, designers of electro-optical imaging systems can take advantage of the reduced Rayleigh scattering of the SWIR band when compared to visible, resulting in higher contrast images through haze, mist, rain, fog and challenging atmospheric conditions. Furthermore, from a military standpoint, SWIR is invisible to the human eye, thus enabling covert operations and is a good choice for targeting with laser rangefinders and designators that transmits between 1060 nm and 1570 nm. A SWIR sensor can also be used in night vision applications taking advantage of an atmospheric phenomenon called night sky radiance (or night glow) that emits five to seven times more illumination than starlight, nearly all of it in the SWIR wavelengths. In a typical airborne application a sensor’s performance is mechanically constrained by the space/volume available and the aperture size limit. This paper describes a model based trade-off methodology to select the optimal Field of View (FOV) for an aperture limited SWIR sensor. This method balances the influences FOV has on sensitivity and resolution. The SWIR sensor’s performance is optimized within mechanical constraints and for the intended application scenarios. In the SWIR band the analysis is expanded to include night time scenarios and laser “see-spot” performance. This model is also adapted for input variable compliance with the industry standard NV-IPM range performance model1 enabling cross-correlation between the two model’s results. An example of a SWIR sensor analysis applying this design model is presented, highlighting the performance advantages that can be gained by maximizing the aperture utilization and choosing the optimal FOV for an imaging sensor when used in airborne targeting applications.
