The Chang’e-4 (CE-4) lunar rover, equipped with a visible and near-IR imaging spectrometer (VNIS) based on acousto-optic tunable filter spectroscopy, was launched to the far side of the moon on December 8, 2018. The detection band of the VNIS ranges from 0.45 to 2.4 μm. Because of the weak reflection of infrared radiation from the lunar surface, a static electronic phase-locked acquisition method is adopted in the infrared channel for signal amplification. In this paper, full-link simulations and modeling are conducted on the infrared channel information flow of the instrument. The signal characteristics of the VNIS are analyzed in depth, and the signal to noise ratio (SNR) prediction and laboratory verification are presented. On 4 January 2019, the VNIS started working successfully and acquired high-resolution spectrum data of the far side of the moon for the first time. Through analysis we have found that the SNR ratio is in line with our predictions, and the data obtained by VNIS in orbit are consistent with the information model proposed in this paper.

Spectrometers based on acousto-optic tunable filters (AOTFs) have several advantages, such as stable temperature adaptability, no moving parts, and wavelength selection through electrical modulation, compared with the traditional grating and Fourier transform spectrometers. Therefore, AOTF spectrometers can realize stable in situ measurement on the lunar surface under wide temperature ranges and low light environments. AOTF imaging spectrometers were first employed for in situ measurement of the lunar surface in the Chinese Chang’e project. The visible and near-infrared imaging spectrometer and the lunar mineralogical spectrometer have been successfully deployed on board the Chang’e-3/4 and Chang’e-5 missions. In this review, we investigate the performance indicators, structural design, selected AOTF performance parameters, data acquisition of the three lunar in situ spectral instruments used in the Chang’e missions. In addition, we also show the scientific achievement of lunar technology based on in situ spectral data.

Compared with hyperspectral remote sensing in visible-light, near infrared and short-wave infrared spectra, hyperspectral remote sensing in the thermal infrared spectrum has unique advantages, especially in the fields of mineral identification and pollution gas. At present, infrared hyperspectral imagers are rare and mainly airborne. In this paper, the basic principle and design features of a newly developed airborne thermal-infrared hyperspectral imaging system (ATHIS) are detailed, and separate validation experiments of laboratory and aerial remote sensing experiments are carried out. Measurements and comparative analysis of infrared emissivity spectra of the typical minerals were performed in the laboratory. In the summer of 2019, the instrument carried out flight tests in Hengdian Town, Dongyang City, Zhejiang Province, China. The results show that ATHIS can also accurately acquire the target emissivity spectrum. In the future, the instrument will also be used to carry out key technology verification and data-processing application research of space infrared hyperspectral imagers plan.

The lunar mineralogical spectrometer (LMS) is the primary scientific payload of the Chang’E-5 mission of the China Lunar Exploration Program. The LMS is responsible for the in situ spectral detection and analysis of the sampling areas of interest on the Moon’s surface. The LMS needs to adapt to a wide range of temperature conditions, varying between the lunar morning to noon, based on the time, location, and work process of the LMS. Thus, ensuring consistency in the spectral data obtained at high temperatures and a wide range of operating environments is a major challenge. In this study, a thermal analysis model of the LMS is built, and the temperature variation of the LMS during its operation on the lunar surface is simulated using the instrument workflow that is based on the simulation results. Independent experiments were also carried out for the temperature-sensitive components in the LMS, and subsequently, the temperature correction model and model coefficients for each temperature-sensitive component were obtained. The final correction result was a quantitative assessment of the ground test data and the in situ lunar detection data. For the ground tests at different temperatures, the average errors were found to be 0.57% and 1.2% for the short- and medium-wave data, respectively, after applying the temperature correction. When the LMS was operating on the lunar surface, the average errors for the short- and medium-ware data after the temperature correction were calculated to be 0.59% and 0.8%, respectively.