Distinguishing the origin of lunar water ice requires in situ isotopic measurements with high sensitivity and robustness under extreme lunar conditions; however, challenges such as uncertain water contents and isotopic fractionation induced by regolith particles restrict isotopic analysis. Herein, we present a miniaturized tunable diode laser absorption spectrometer (TDLAS) developed as the core prototype for the Chang'E-7 Lunar Soil Water Molecule Analyzer (LSWMA). The wavelength range of the instrument is 3659.5-3662.0 cm-1, and the system integrates a Herriott cell for stable multi-isotope (H2 16O, H2 18O, H2 17O, and HD16O) detection and employs regolith samples of known isotopic experiments to quantify adsorption-induced fractionation. Performance evaluations demonstrated a dynamic water detection range of 0.01-2 wt % and isotope precision up to 1.3 parts per thousand for delta D (30.5 s), 0.77 parts per thousand for delta 18O (36 s), and 0.75 parts per thousand for delta 17O (21.5 s) with extended averaging. Repeated injections of three types of standard water revealed a volume-dependent deviation (Delta delta D up to -59.5 parts per thousand) attributed to multilayer adsorption effects, while simulated lunar soil experiments identified additional isotopic fractionation (Delta delta D up to -12.8 parts per thousand) caused by particle binding. These results validate the ability of the spectrometer to resolve subtle isotopic shifts under lunar conditions, providing critical data for distinguishing water origins and advancing future resource utilization strategies.

Detection of water-ice deposits using synthetic aperture radar (SAR) is a cost-effective, and efficient approach to understand lunar water resources. As water is crucial to supporting human-based space exploration, current and near upcoming lunar missions are primary concentrated on mapping and quantification of water ice exposures on surface and subsurface levels. The circular polarization ratio greater than one (CPR >1) derived using the orbital radar observations is considered as an important SAR derived parameter for water-ice detection. This study aims to investigate 14 craters near the lunar poles with high CPR (CPR >1), as identified in previous studies, using the L-band (24 cm) dual frequency synthetic aperture radar (DFSAR) onboard Chandrayaan-2. In addition to CPR, we computed the degree of polarization (DOP) after applying parallax error correction that helps in reducing misinterpretation. Our findings are based on orthorectified DFSAR calibrated data analysis. We found that the CPR of crater interiors is not significantly different from that of their surroundings, and this pattern is consistent throughout all the 14 craters selected. Further, we also found a linear inverse relationship between CPR and DOP for the interior and exteriors of the craters, with R-2 0.99, indicating a strong correlation between these two parameters. We found only 2 % of total pixels are above CPR > 1, which indicates that there is less possibility of homogeneous water-ice but the possibility of water-ice mixed with the subsurface regolith cannot be ruled out.

The presence of water in lunar materials can significantly impact the evolution of lunar geology and environment, as well as provide necessary conditions for the utilization of lunar resources. However, due to the limitations of lunar remote sensing methods, it is challenging to obtain direct evidence of water or determine its form of occurrence. Laser Raman spectroscopy, on the other hand, can provide valuable information on the type, distribution, and content of water in lunar materials without the need for illumination, sample pretreatment, or destructive measures. In this study, we utilized Raman spectroscopy to detect and quantify the water-containing characteristics of typical lunar rocks and minerals, including adsorbed water, ice, crystalline water, and hydroxyl-structured water. First, we used a 532 nm laser micro-Raman spectroscopy to identify and analyze the water-containing signals of various forms of water in lunar soil simulants. We then examined and analyzed the detection limits of adsorbed water, crystalline water, and hydroxyl- structured water in these simulants, as well as the relationship between their content and signal intensity. Finally, we employed linear regression (LR), ridge regression (RR), and partial least squares regression (PLSR) to quantitatively analyze the contents of these three forms of water in the lunar soil simulants. Our results demonstrate that the characteristic spectral peaks of the four forms of water in the lunar soil simulants can be clearly identified, with peak distribution regions located at 100-1 700 cm(-1) and 2 600-3 900 cm(-1) for the lunar soil components and water bodies, respectively. The spectral peaks of water are a combination of broad envelope peaks of hydrogen-bonded OH and sharp peaks of non- hydrogen-bonded OH stretching vibrations in varying proportions. The detection limits for adsorbed water, crystalline water (MgSO47H(2)O), and hydroxyl water (Al2Si2O5(OH)(4)) in the lunar soil simulants are 1.3 wt%, 0. 8 wt%, and 0. 3 wt%, respectively. There is a linear relationship between the intensity of water-containing peaks and the water content in the lunar soil simulants, with root mean square errors of 1. 75 wt%, 1. 16 wt%, and 1. 19 wt% obtained through LR, RR, and PLSR.

To confirm the presence of water on the moon, many scientists of the world are making continuous efforts through remote sensing data of different missions. In this direction, the Dual Frequency Synthetic Aperture Radar (DFSAR) sensor of the Chandrayaan-2 mis-sion adds a very important chapter which is the world's first Planetary SAR mission of fully polarimetric capability with L-and S-band. This study utilizes the L-band fully polarimetric DFSAR data of Chandrayaan-2 mission for the PolSAR parameters-based analysis and ice detection in permanently shadowed regions (PSRs) of the lunar South Polar craters. The PSR IDs SP_875930_3125710, SP_837670_3387710, and SP_874930_3578760 of the lunar South Pole were selected for the polarimetric analysis using DFSAR L -band. Based on previous studies ((Li et al., 2018), two out of three PSR Ids (SP_875930_3125710 and SP_874930_3578760) were easy to identify for surface ice. That is why only two PSR IDs were used for polarimetric SAR analysis of DFSAR data for surface ice char-acterization and detection. The hybrid polarimetric simulation was also performed to the fully polarimetric L-band data to study stokes vectors and associated child parameters for the selected study area. The analysis of polarimetric distortions confirms the persistence of the polarimetric quality of the SAR data and for this, the polarimetric distortion analysis was performed with co-pol and cross-pol chan-nels. Wave dichotomy-based Huynen decomposition and Barnes decomposition models were implemented to the fully polarimetric quad-pol DFSAR data. The eigenvalue-eigenvector-based decomposition model was also implemented to characterize the scattering behavior of the PSRs. A high correlation was obtained between Circular Polarization Ratio (CPR), entropy, and alpha for the 200 hundred points randomly collected from the image. Diversity index also showed a high positive correlation with CPR. The polarimetric quality of the data was evaluated with the scatterplot between the cross-polarimetric channels and it was observed that the L-band quad-pol data of DFSAR satisfies the criteria for PolSAR data of a monostatic SAR system. Analysis of the results obtained from the polarimetric SAR data indicated that the high volumetric scattering and CPR for the PSR ID SP_875930_3125710 may be due to ice clusters within the permanently shadowed region. Polarimetric analysis of the PSR (SP_874930_3578760) at Howarth Crater using L-band DFSAR data shows a low amount of volumetric scattering and a low CPR for most locations in the PSR. The different ranges of CPR and volume scattering for both craters indicate that polarimetric parameters and indices should be studied in conjunction with geomorphological parameters of the lunar surface, for unambiguous identification of surface ice clusters in the PSR. (c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

A proof of concept for a frost detection imager using reflected starlight is presented; the limitations of this technique are explored experimentally. An ice-covered lunar surface is simulated inside a vacuum chamber, which is then illuminated with a lamp containing UV and visible output to simulate the wavelengths of the background starfield. The simulated lunar surface is imaged with a camera utilizing a UV and visible filter pairing. At Lyman-alpha wavelengths, ice has low reflectivity, and on average appears darker than the regolith in the UV image. In visible wavelengths, this behavior is reversed, with ice appearing brighter than regolith. UV/VIS image ratioing is subsequently performed in order to discern frost from the lunar regolith simulant in order to demonstrate the capability of this technology for locating the presence of ice on the lunar surface. When the two images are ratioed, the signal to noise ratio to distinguish ice from regolith improves by 36%. In cases where the presence of shadows and specular reflection make distinguishing ice from regolith in either a single UV or visible image difficult, ratioing the images makes the distinction clear.

Published literature suggests that water ice might be unambiguously detected in the presence of background contaminants by developing a frequency swept sensor to obtain the dielectric spectrum. Such a sensor could be incorporated into the tip of a spike and driven into the lunar regolith to detect moisture as a function of depth. A sensor was created to test this concept for varying concentrations of ice in lunar soil simulant under vacuum conditions. Ice relaxation occurs at frequencies well below 1 Hz at temperatures present on the Lunar surface, making it difficult to distinguish ice from the surrounding regolith. So, a heating element was incorporated with the sensor to capture the dielectric spectra as the ice warms, allowing the relaxation to be detected in a shorter period of time. The test results show the ability of this sensor to detect the presence of varying quantities of ice in the soil simulant and the need for more complex non-linear mixing models to quantify the amount of ice present in the mixture. Published by Elsevier Ltd.

We have employed the Arecibo Observatory Planetary Radar (AO) transmitter and the Mini-RF radar onboard NASA's Lunar Reconnaissance Orbiter (LRO) as a receiver to collect bistatic data of the lunar surface. In this paper, we demonstrate the ability to form bistatic polarimetric imagery with spatial resolution on the order of 50m, and to create polarimetric maps that could potentially reveal the presence of ice in lunar permanently shadowed craters. We discuss the details of the signal processing techniques that are required to allow these products to be formed.