Active and thermal imaging performance under bad weather conditions

Thermal imaging cameras are widely used in military contexts for their night vision capabilities and their observation range; there are based on passive infrared sensors (e.g. MWIR or LWIR range). Under bad weather conditions or when the target is partially hidden (e.g. foliage, military camouflage) they are more and more complemented by active imaging systems, a key technology to perform target identification at long range. The 2D flash imaging technique is based on a high powered pulsed laser source that illuminates the entire scene and a fast gated camera as the imaging system. Both technologies are well experienced under clear meteorological conditions; models including atmospheric effects such as turbulence are able to predict accurately their performances. However, under bad weather conditions such as rain, haze or snow, these models are not relevant. This paper introduces new models to predict performances under bad weather conditions for both active and infrared imaging systems. We first establish an enumeration of these “bad” atmospheric conditions, depending on their occurrence rate. Then we develop physical models to describe their intrinsic characteristics and their impact on the imaging system performances. Finally, we approximate these models to have a “first order” model easy to deploy for industrial applications. This theoretical work will be validated on real active and infrared data

Experiments and Models of Active and Thermal Imaging Under Bad Weather Conditions

Thermal imaging cameras are widely used in military contexts for their night vision capabilities and their observation range; there are based on passive infrared sensors (e.g. MWIR or LWIR range). Under bad weather conditions or when the target is partially hidden (e.g. foliage, military camouflage) they are more and more complemented by active imaging systems, a key technology to perform target identification at long range. The 2D flash imaging technique is based on a high powered pulsed laser source that illuminates the entire scene and a fast gated camera as the imaging system. Both technologies are well experienced under clear meteorological conditions; models including atmospheric effects such as turbulence are able to predict accurately their performances. However, under bad weather conditions such as rain, haze or snow, these models are not relevant. This paper introduces new models to predict performances under bad weather conditions for both active and infrared imaging systems. We point out their effects on controlled physical parameters (extinction, transmission, spatial resolution, thermal background, speckle, turbulence). Then we develop physical models to describe their intrinsic characteristics and their impact on the imaging system performances. Finally, we approximate these models to have a “first order” model easy to deploy for industrial applications. This theoretical work will be validated on real active and infrared data

CARS, THE ONLY TOOL FOR THE DIAGNOSTICS OF REACTIVE MEDIA ?

La Diffusion Raman anti-Stokes Cohérents (DRASC) est une technique bien adaptée à la mesure des températures et concentrations moléculaires dans les milieux en réaction. Les principes généraux sont exposés, ainsi que les caractéristiques techniques les plus importantes. Les exemples d'application les plus significatifs sont décrits, de façon à présenter le niveau actuel de performance : temps de mesure, résolution spatiale, sensibilité de détection. La mesure de température instantanée dans un moteur à piston, l'étude des produits de photolyse de H2CO et la DRASC résonnante sur C2 sont discutés.Coherent anti-Stokes Raman scattering (CARS) is well adapted to the measurement of temperatures and concentrations of molecules in reactive gaseous media. The general principles are given along with the major technical advantages and requirements. Characteristic applications are described in order to present state of the art performance levels : measurement time, spatial resolution, detection sensitivity. Instantaneous temperature measurements in a piston engine, analysis of photolysis products of H2CO and resonance-enhanced CARS of C2 are discussed

Toward a combustion-driven mixing GDL

The influence of various pollutants on the ONERA CO2/N 2/He mixing GDL is evaluated. Special attention is paid to those chemicals likely to appear in a combustion-driven system. For our plenum conditions (12 atm, 3 000 K), it is found that at most 5 % H2O, 10 % H2, or 15 % CO2 by volume can be tolerated among combustion products. It is also observed that CO has a large effect on gain due to lack of coupling to CO2. If the CO fraction is large, N2O proves superior to CO2 for laser action on the small-scale device used

SPECTROSCOPIE RAMAN COHÉRENTE DANS UN RÉACTEUR CVD

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Rotational relaxation model for CO-N2_{2}. Prediction of CARS profiles and comparison with experiment

The CO $v = 1 \leftarrow 0$ Q-branch perturbed by CO and N$_{2}$ has been recorded using Coherent Anti-Stokes Raman Spectroscopy (CARS) at room temperature between 1 and 20 atmosphere. Collisional broadening coefficients calculated with a semiclassical theory have been inverted to obtain the rotationally inelastic state-to-state rate constants, using the Modified Energy Gap (MEG) law. The resulting theoretical collisionally narrowed Q-branch profiles are in agreement with the experimental spectra.Le spectre de diffusion Raman Anti-Stokes Cohérente (DRASC) de la branche Q fondamentale de CO pur et perturbé par N$_{2}$ a été enegistré à température ordinaire entre 1 et 20 atmosphères. Les coefficients d'élargissement collisionnel ont été calculés à partir d'une approche semi-classique. Les taux de transferts rotationnels d'état-à-état ont été calculés à l'aide d'un modèle relaxationnel par inversion des coefficients d'élargissement. Les prédictions de ce modèle sont en accord satisfaisant avec les spectres DRASC expérimentaux