The reduced Rayleigh scattering of SWIR radiation, when compared to the visible and NIR band, can be exploited to obtain higher contrast images even under challenging atmospheric conditions. Additionally the SWIR band neatly covers the most popular wavelengths used for laser designation and ranging, and hence SWIR imagers can be used to target and detect these sources. A SWIR sensor can also be used in night vision applications by 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. This paper presents a radiometry model intended for the design and analysis of a SWIR imaging sensor that is expanded to included night-time scenarios and laser “see-spot” range performance. The model is also adapted for input variable compliance with the industry standard NV-IPM range performance model, thereby enabling cross-correlation between the range performance predictions of the two models’ results. Some SWIR sensor design examples that trade off the imaging range performance and the “see-spot” range performance are presented, and the results are discussed.
The focal plane array in an MWIR camera should be configured optimally in terms of readout mode, stare time and gain setting to achieve the best (minimum) noise levels and/or maximal usable dynamic range under variable environmental conditions. In a long-range observation system noise is normally dominated by the environment, with optical contributions due to ambient illumination, target and background radiance, atmospheric transmission, path radiance, optics transmission and optics radiance. This optical signal is then detected according to the FPA spectral responsivity, which, combined with electronic contributors such as read noise, amplifier noise, clock noise, and quantization noise, eventually result in a digital output signal. A complete radiometric system modelling approach is used to predict the system NETD under a variety of representative environmental conditions and target ranges, which can then be used to inform decisions regarding the selection of the detector readout mode and gain mode, as well as setting the stare time for best operational performance. Results are presented demonstrating the effects of the various environmental factors and system parameters on NETD.
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.
As pixel sizes reduce in the development of modern High Definition (HD) Mid Wave Infrared (MWIR) detectors the interpixel cross-talk becomes increasingly difficult to regulate. The diffusion lengths required to achieve the quantum efficiency and sensitivity of MWIR detectors are typically longer than the pixel pitch dimension, and the probability of inter-pixel cross-talk increases as the pixel pitch/diffusion length fraction decreases. Inter-pixel cross-talk is most conveniently quantified by the focal plane array sampling Modulation Transfer Function (MTF). Cross-talk MTF will reduce the ideal sinc square pixel MTF that is commonly used when modelling sensor performance. However, cross-talk MTF data is not always readily available from detector suppliers, and since the origins of inter-pixel cross-talk are uniquely device and manufacturing process specific, no generic MTF models appear to satisfy the needs of the sensor designers and analysts. In this paper cross-talk MTF data has been collected from recent publications and the development for a generic cross-talk MTF model to fit this data is investigated. The resulting cross-talk MTF model is then included in a MWIR sensor model and the impact on sensor performance is evaluated in terms of the National Imagery Interoperability Rating Scale’s (NIIRS) General Image Quality Equation (GIQE) metric for a range of fnumber/ detector pitch Fλ/d configurations and operating environments. By applying non-linear boost transfer functions in the signal processing chain, the contrast losses due to cross-talk may be compensated for. Boost transfer functions, however, also reduce the signal to noise ratio of the sensor. In this paper boost function limits are investigated and included in the sensor performance assessments.
Detailed radiometric analysis has shown that 3-5 µm medium wave infrared (MWIR) staring array well fill quickly reaches very high percentages, once hot optics, path radiance and inefficient f-number matching are taken into account. Well fill values of 90% plus are not unheard of. Likewise, the sensor noise eats away at the sensitivity. Therefore, it would appear that the very small signals often sought might not get sufficient dynamic bit-range to describe small signal flux propagating through poor atmospheres. This work presents a very detailed real-world model that includes all known factors that might compete for the bit resolution in a digitized sensor signal. The effect of different scene temperatures, atmospheric conditions and sensor design characteristics are briefly investigated. The effect of the various well fill contributors are shown in relation to each other in order to build an understanding of the nature of the total well fill. Finally, some mitigation measures are described to limit the negative effects of undue large well fill.
With 640x512 pixel format IR detector arrays having been on the market for the past decade, Standard Definition (SD)
thermal imaging sensors have been developed and deployed across the world. Now with 1280x1024 pixel format IR
detector arrays becoming readily available designers of thermal imager systems face new challenges as pixel sizes reduce
and the demand and applications for High Definition (HD) thermal imaging sensors increases. In many instances the
upgrading of existing under-sampled SD thermal imaging sensors into more optimally sampled or oversampled HD
thermal imaging sensors provides a more cost effective and reduced time to market option than to design and develop a
completely new sensor.
This paper presents the analysis and rationale behind the selection of the best suited HD pixel format MWIR detector for
the upgrade of an existing SD thermal imaging sensor to a higher performing HD thermal imaging sensor. Several
commercially available and “soon to be” commercially available HD small pixel IR detector options are included as part
of the analysis and are considered for this upgrade. The impact the proposed detectors have on the sensor’s overall
sensitivity, noise and resolution is analyzed, and the improved range performance is predicted. Furthermore with reduced
dark currents due to the smaller pixel sizes, the candidate HD MWIR detectors are operated at higher temperatures when
compared to their SD predecessors. Therefore, as an additional constraint and as a design goal, the feasibility of
achieving upgraded performance without any increase in the size, weight and power consumption of the thermal imager
is discussed herein.
The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor’s sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system’s performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.
`KENIS', a complete, high performance, compact and lightweight thermal imager, is built around the `OSPREY' infrared detector from BAE systems Infrared Ltd. The `OSPREY' detector uses a 384 X 288 element CMT array with a 20 micrometers pixel size and cooled to 120 K. The relatively small pixel size results in very compact cryogenics and optics, and the relatively high operating temperature provides fast start-up time, low power consumption and long operating life. Requiring single input supply voltage and consuming less than 30 watts of power, the thermal imager generates both analogue and digital format outputs. The `KENIS' lens assembly features a near diffraction limited dual field-of-view optical system that has been designed to be athermalized and switches between fields in less than one second. The `OSPREY' detector produces near background limited performance with few defects and has special, pixel level circuitry to eliminate crosstalk and blooming effects. This, together with signal processing based on an effective two-point fixed pattern noise correction algorithm, results in high quality imagery and a thermal imager that is suitable for most traditional thermal imaging applications. This paper describes the rationale used in the development of the `KENIS' thermal imager, and highlights the potential performance benefits to the user's system, primarily gained by selecting the `OSPREY' infra-red detector within the core of the thermal imager.