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

Ongoing nationwide outbreak of Salmonella Agona associated with internationally distributed infant milk products, France, December 2017

International audienceOn 1 December 2017, an outbreak of Salmonella Agona infections among infants was identified in France. To date, 37 cases (median age: 4 months) and two further international cases have been confirmed. Five different infant milk products manufactured at one facility were implicated. On 2 and 10 December, the company recalled the implicated products; on 22 December, all products processed at the facility since February 2017. Trace-forward investigations indicated product distribution to 66 countries