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Spectral Characterization of the AisaOWL.

Authors :
Harris, Laura
Warren, Mark
Grant, Mike
Llewellyn, Gary M
Source :
IEEE Transactions on Geoscience & Remote Sensing; May2017, Vol. 55 Issue 5, p2751-2756, 6p
Publication Year :
2017

Abstract

The AisaOWL is a recent-to-market thermal hyperspectral instrument. As such, there is little information about the sensor performance in the literature. The sensor covers the 7.6– 12.6~\mu \textm part of the long-wave infrared region with 102 continuous bands, and is capable of imaging in low-light conditions. This paper presents an independent characterization of the AisaOWL sensor, examining the spectral accuracy of black body measurements at different temperatures and validating manufacturer recommendations for warm-up, integration, and calibration times. This analysis is essential for establishing high quality operational procedures and in giving confidence to users of the data. In this paper, the sensor has been found to have a maximum error of 2 °C in absolute temperature measurement, and provides spectra most accurate in the 8– 9~\mu \textm region. The recommended warm-up time of 15 min has been confirmed, with a 1% increase in error identified for data collected only 7 min after switch on. The optimal integration time of 1.18 ms has been validated and an exponential decrease in performance observed outside the 0.85–1.2 ms range. The detector used by the sensor is shown to have stability issues and this has been examined by comparing black body data processed with different calibration data. While the detector is operating in a stable regime compatible with the calibration, these black body readings stay within 5% across the central bands, approaching 10% below 8~\mu \textm and just exceeding 20% above 11 \mu \textm . [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
55
Issue :
5
Database :
Complementary Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
124146478
Full Text :
https://doi.org/10.1109/TGRS.2017.2653241