Recent European atmospheric imaging missions have seen a move towards the use of CMOS sensors for the visible and NIR parts of the spectrum. These applications have particular challenges that are completely different to those that have driven the development of commercial sensors for applications such as cell-phone or SLR cameras. This paper will cover the design and performance of general-purpose image sensors that are to be used in the MTG (Meteosat Third Generation) and MetImage satellites and the technology challenges that they have presented. We will discuss how CMOS imagers have been designed with 4T pixel sizes of up to 250 μm square achieving good charge transfer efficiency, or low lag, with signal levels up to 2M electrons and with high line rates. In both devices a low noise analogue read-out chain is used with correlated double sampling to suppress the readout noise and give a maximum dynamic range that is significantly larger than in standard commercial devices. Radiation hardness is a particular challenge for CMOS detectors and both of these sensors have been designed to be fully radiation hard with high latch-up and single-event-upset tolerances, which is now silicon proven on MTG. We will also cover the impact of ionising radiation on these devices. Because with such large pixels the photodiodes have a large open area, front illumination technology is sufficient to meet the detection efficiency requirements but with thicker than standard epitaxial silicon to give improved IR response (note that this makes latch up protection even more important). However with narrow band illumination reflections from the front and back of the dielectric stack on the top of the sensor produce Fabry-Perot étalon effects, which have been minimised with process modifications. We will also cover the addition of precision narrow band filters inside the MTG package to provide a complete imaging subsystem. Control of reflected light is also critical in obtaining the required optical performance and this has driven the development of a black coating layer that can be applied between the active silicon regions.
The Reststrahlen effect has been investigated for detecting regions of recently disturbed earth, by taking images where
metallic objects had been buried in a sandy soil and comparing with images of undisturbed soil. The images were taken
with a Long wave Infrared (LWIR) Hyperspectral Sensor, the Hyper-Cam.
Benefits for the detection of difficult targets have been demonstrated for multispectral and polarimetric imagery in differing conditions. The spectral differences between target and background have been seen to provide an enhancement to target discrimination. However, false alarms can occur mainly due to spectral variations in background materials. Complimentarily, polarimetric imagery has been used to detect man made targets by exploiting the reflective characteristics of man-made objects and the suppression of background clutter; but the detection process can be limited by the geometry and nature of targets. A data gathering SWIR Multispectral-Polarimetric sensor has been built to investigate whether adding polarimetric to multispectral information decreases background induced false alarms whilst maintaining good detection statistics for low contrast targets.
The detection of long range air targets in a Naval scenario using passive Imaging IR sensor is a task of primary importance for current and next generation Naval equipment. The authors have investigated Dynamic Programming based target detection systems utilizing the output of an image filter as the input to a likelihood classifier based on intensity alone. Variations of this technique have been proven to offer high sensitivity to dim targets though environmental characteristics in the Naval scenario can give rise to clutter induced false alarms. The work presented herein investigates augmentation of the intensity classifier with textural analysis techniques on IR imagery in the 3-5 micron waveband to assist in false alarm discrimination. It is shown that augmentation with a textural classifier can improve rejection of false alarms due to clutter. This work is apt of an ongoing program of IRST and Surveillance Sensor processing development.
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