Optical remote sensing of the earth from air and space typically utilizes several channels in the visible and near infrared spectrum. Thin-film optical interference filters, mostly of narrow bandpass type, are applied to select these channels. The filters are arranged in filter wheels, arrays of discrete stripe filters mounted in frames, or patterned arrays on a monolithic substrate. Such multi-channel filter assemblies can be mounted close to the detector, which allows a compact and lightweight camera design. Recent progress in image resolution and sensor sensitivity requires improvements of the optical filter performance. Higher demands placed on blocking in the UV and NIR and in between the spectral channels, in-band transmission and filter edge steepness as well as scattering lead to more complex filter coatings with thicknesses in the range of 10 - 25μm. Technological limits of the conventionally used ion-assisted evaporation process (IAD) can be overcome only by more precise and higher-energetic coating technologies like plasma-assisted reactive magnetron sputtering (PARMS) in combination with optical broadband monitoring. Optics Balzers has developed a photolithographic patterning process for coating thicknesses up to 15μm that is fully compatible with the advanced PARMS coating technology. This provides the possibility of depositing multiple complex high-performance filters on a monolithic substrate. We present an overview of the performance of recently developed filters with improved spectral performance designed for both monolithic filter-arrays and stripe filters mounted in frames. The pros and cons as well as the resulting limits of the filter designs for both configurations are discussed.
Jan Broßmann, Thorsten Best, Thomas Bauer, Stefan Jakobs, and Thomas Eisenhammer, "Low-loss interference filter arrays made by plasma-assisted reactive magnetron sputtering (PARMS) for high-performance multispectral imaging," Proc. SPIE 10000, Sensors, Systems, and Next-Generation Satellites XX, 100001E (Presented at SPIE Remote Sensing: September 28, 2016; Published: 19 October 2016); https://doi.org/10.1117/12.2241069.
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