Detection Capability Evaluation of Lunar Mineralogical Spectrometer: Results from Ground Experimental Data

The Chang’E-6 mission will first land on the far side of the moon and bring lunar samples back. As a hyperspectral imager aboard the Chang’E-6 lander, the Lunar Mineralogical Spectrometer (LMS), will achieve the goal of spectral detection and mineral composition analysis in the sampling area, and th...

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Veröffentlicht in:Research in astronomy and astrophysics 2023-12, Vol.23 (12), p.125013-174
Hauptverfasser: Gao, Fang, Liu, Bin, Ren, Xin, Liu, Da-Wei, Li, Chun-Lai
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Sprache:eng
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Zusammenfassung:The Chang’E-6 mission will first land on the far side of the moon and bring lunar samples back. As a hyperspectral imager aboard the Chang’E-6 lander, the Lunar Mineralogical Spectrometer (LMS), will achieve the goal of spectral detection and mineral composition analysis in the sampling area, and the data of LMS will also be compared with the results of the returned sample laboratory measurements. Visible and near-infrared hyperspectral remote sensing is an effective tool for lunar minerals identification and quantification. The ground validation experiment can be used to evaluate the detection ability of the LMS. According to the modal abundances of lunar minerals and glasses of APOLLO samples, binary mixed samples, ternary mixed samples, and seven-membered mixed samples were prepared. The samples were ground and stirred homogeneous to about 200 mesh (median particle size about 75 μ m), to simulate the soil state of the lunar surface. Under the laboratory ambient condition, the 480–3200 nm spectral data of the samples were acquired using the Engineering Qualification Model (EQM) of Chang’E-5 LMS, the performance of which is consistent with the flight model of Chang’E-6 LMS. By fitting the mixed samples’ spectral data of the EQM using the Modified Gaussian Methods, the following conclusions can be drawn: The subtle spectral changes of mixed samples can be detected. The modal abundance of low-Ca pyroxene, high-Ca pyroxene, and plagioclase can be derived based on the spectral parameters such as absorption position, depth or width of the mixed samples, and the correlation coefficients R 2 are better than 82%, indicating that the LMS has good quantitative detection capability.
ISSN:1674-4527
2397-6209
DOI:10.1088/1674-4527/acfd03