Influence of technology on FLIR waveband selection

Herbert M. Runciman

doi:10.1117/12.210045

22 May 1995 Influence of technology on FLIR waveband selection

Herbert M. Runciman

Proceedings Volume 2470, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI; (1995) https://doi.org/10.1117/12.210045
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

The choice of waveband for thermal imaging depends not only on the characteristics of the target, background and atmosphere, but on imager parameters such as electron storage capacity per pixel, frame rate, optical transmission, cold-shield efficiency and non-uniformity. This paper outlines the ways in which the conventional trade-offs of sensitivity against imager and scene parameters are modified when electron storage capacity and non-uniformity are taken into account. In the presence of these limitations, the emphasis is frequently on optimizing image contrast rather than signal level or even photon-limited signal/noise ratio (SNR), resulting in more severe degradations due to equipment limitations such as transmission of hot windows or cold-shield inefficiency, and in reduced spectral bandwidths for optimum sensitivity. The dependence of sensitivity on cut-off wavelength is illustrated for a range of imager parameters, and the benefits of cooled or pseudo-cooled spectral filters are discussed. Optimum cut-off wavelength, particularly in the 3 - 5 micrometers (MWIR) band is found to depend strongly on system parameters. Comparisons are made between scanning and staring systems. In the 8 - 12 micrometers (LWIR) band scanning systems can compete well with staring arrays for equivalent frame rates, but improvements in multiplexer technology to give higher storage capacity or faster read-out will increasingly favor staring systems for all bands.

Citation Download Citation

Herbert M. Runciman "Influence of technology on FLIR waveband selection", Proc. SPIE 2470, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI, (22 May 1995); https://doi.org/10.1117/12.210045

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