Thermal Imaging Performance of TIR Onboard the Hayabusa2 Spacecraft

作者: Takehiko Arai , Tomoki Nakamura , Satoshi Tanaka , Hirohide Demura , Yoshiko Ogawa

DOI: 10.1007/S11214-017-0353-9

关键词:

摘要: The thermal infrared imager (TIR) is a camera onboard the Hayabusa2 spacecraft. TIR will perform thermography of C-type asteroid, 162173 Ryugu (1999 JU3), and estimate its surface physical properties, such as emissivity \(\epsilon \), roughness, inertia \(\varGamma through remote in-situ observations in 2018 2019. In prelaunch tests TIR, detector calibrations evaluations, along with imaging demonstrations, were performed. present paper introduces experimental results test conducted using large-aperture collimator conjunction under atmospheric conditions. A blackbody source, controlled at constant temperature, was measured order to construct calibration curve for obtaining temperatures from observed digital data. As known target, sandblasted black almite plate warmed back flexible heater by evaluate accuracy curve. an analog target carbonaceous chondrites (\(50~\mbox{mm} \times 2~\mbox{mm}\) thickness) also clarify performance TIR. curve, which fitted specific model Planck function, allowed conversion temperature within error 1 ∘C (\(3\sigma \) standard deviation) range 30 100 ∘C. consistent K-type thermocouples, when variation exhibited random 0.3 (\(1\sigma \)) each pixel 50 can resolve fine structure meteorites, including cracks pits specified field view 0.051∘ (\(328 248~\mbox{pixels}\)). There spatial distributions 3 setting images obtained If distribution caused emissivity, effects difference \(\Delta \epsilon estimated be approximately 0.08, calculated Stefan-Boltzmann raw. Otherwise, if inertia, \varGamma \(150~\mbox{J}\,\mbox{m}^{-2}\,\mbox{s}^{0.5}\,\mbox{K}^{-1}\), based on simulation 20-layer heat balance equation. meteorite experiments indicates that asteroid accuracies \cong 0.02\) 20~\mbox{J}\,\mbox{m}^{-2}\,\mbox{s}^{0.5}\,\mbox{K}^{-1}\), respectively. However, degenerate Therefore, observe same areas numerous times (\({>}10\) times, ensure statistical significance), allows us determine both parameters least-squares fitting Ryugu.

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