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Appl. Sci. 2017, 7(11), 1165;

Atmospheric Attenuation Correction Based on a Constant Reference for High-Precision Infrared Radiometry

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 13033, China
University of Chinese Academy of Sciences, Beijing 100049, China
Author to whom correspondence should be addressed.
Received: 11 September 2017 / Revised: 6 November 2017 / Accepted: 9 November 2017 / Published: 13 November 2017
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Infrared (IR) radiometry technology is an important method for characterizing the IR signature of targets, such as aircrafts or rockets. However, the received signal of targets could be reduced by a combination of atmospheric molecule absorption and aerosol scattering. Therefore, atmospheric correction is a requisite step for obtaining the real radiance of targets. Conventionally, the atmospheric transmittance and the air path radiance are calculated by an atmospheric radiative transfer calculation software. In this paper, an improved IR radiometric method based on constant reference correction of atmospheric attenuation is proposed. The basic principle and procedure of this method are introduced, and then the linear model of high-speed calibration in consideration of the integration time is employed and confirmed, which is then applicable in various complex conditions. To eliminate stochastic errors, radiometric experiments were conducted for multiple integration times. Finally, several experiments were performed on a mid-wave IR system with Φ600 mm aperture. The radiometry results indicate that the radiation inversion precision of the novel method is 4.78–4.89%, while the precision of the conventional method is 10.86–13.81%. View Full-Text
Keywords: Infrared (IR) radiometry; atmospheric attenuation; blackbody; radiation inversion Infrared (IR) radiometry; atmospheric attenuation; blackbody; radiation inversion

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Huang, Z.; Yin, L.; Wang, J.; Li, H. Atmospheric Attenuation Correction Based on a Constant Reference for High-Precision Infrared Radiometry. Appl. Sci. 2017, 7, 1165.

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