Thermal modeling of the lunar regolith at the Chang'E‐4 landing site

2021 ◽  
Author(s):  
Honglei Lin ◽  
Shuai Li ◽  
Yangting Lin ◽  
Yang Liu ◽  
Yong Wei ◽  
...  
Keyword(s):  
Thermal Modeling ◽  
Lunar Regolith ◽  
Landing Site

scholarly journals Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Hanjie Song ◽  
Chao Li ◽  
Jinhai Zhang ◽  
Xing Wu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Electromagnetic Waves ◽  
Lunar Regolith ◽  
Landing Site ◽  
Rock Properties ◽  
The Moon ◽  
Local Correlation ◽  
Near Surface ◽  
Property Analysis ◽  
Stratigraphic Division ◽  
Formation And Evolution

The Lunar Penetrating Radar (LPR) onboard the Yutu-2 rover from China’s Chang’E-4 (CE-4) mission is used to probe the subsurface structure and the near-surface stratigraphic structure of the lunar regolith on the farside of the Moon. Structural analysis of regolith could provide abundant information on the formation and evolution of the Moon, in which the rock location and property analysis are the key procedures during the interpretation of LPR data. The subsurface velocity of electromagnetic waves is a vital parameter for stratigraphic division, rock location estimates, and calculating the rock properties in the interpretation of LPR data. In this paper, we propose a procedure that combines the regolith rock extraction technique based on local correlation between the two sets of LPR high-frequency channel data and the common offset semblance analysis to determine the velocity from LPR diffraction hyperbola. We consider the heterogeneity of the regolith and derive the relative permittivity distribution based on the rock extraction and semblance analysis. The numerical simulation results show that the procedure is able to obtain the high-precision position and properties of the rock. Furthermore, we apply this procedure to CE-4 LPR data and obtain preferable estimations of the rock locations and the properties of the lunar subsurface regolith.

Dielectric properties estimation of the lunar regolith at CE-3 landing site using lunar penetrating radar data

Icarus ◽  
2017 ◽  
Vol 284 ◽  
pp. 424-430 ◽  
Author(s):  
Jianqing Feng ◽  
Yan Su ◽  
Chunyu Ding ◽  
Shuguo Xing ◽  
Shun Dai ◽  
...  
Keyword(s):  
Dielectric Properties ◽  
Lunar Regolith ◽  
Landing Site ◽  
Radar Data

scholarly journals Volcanic history of the Imbrium basin: A close-up view from the lunar rover Yutu

2015 ◽  
Vol 112 (17) ◽  
pp. 5342-5347 ◽  
Author(s):  
Jinhai Zhang ◽  
Wei Yang ◽  
Sen Hu ◽  
Yangting Lin ◽  
Guangyou Fang ◽  
...  
Keyword(s):  
Lunar Regolith ◽  
Landing Site ◽  
Lunar Soil ◽  
Lunar Rover ◽  
Surface Exploration ◽  
Mantle Reservoir ◽  
History Of ◽  
Radar Measurements ◽  
Residual Melt

We report the surface exploration by the lunar rover Yutu that landed on the young lava flow in the northeastern part of the Mare Imbrium, which is the largest basin on the nearside of the Moon and is filled with several basalt units estimated to date from 3.5 to 2.0 Ga. The onboard lunar penetrating radar conducted a 114-m-long profile, which measured a thickness of ∼5 m of the lunar regolith layer and detected three underlying basalt units at depths of 195, 215, and 345 m. The radar measurements suggest underestimation of the global lunar regolith thickness by other methods and reveal a vast volume of the last volcano eruption. The in situ spectral reflectance and elemental analysis of the lunar soil at the landing site suggest that the young basalt could be derived from an ilmenite-rich mantle reservoir and then assimilated by 10–20% of the last residual melt of the lunar magma ocean.

Lunar regolith and substructure at Chang’E-4 landing site in South Pole–Aitken basin

2020 ◽  
Author(s):  
Jinhai Zhang ◽  
Bin Zhou ◽  
Yangting Lin ◽  
Meng-Hua Zhu ◽  
Hanjie Song ◽  
...  
Keyword(s):  
Lunar Regolith ◽  
Landing Site ◽  
South Pole

Lunar regolith and substructure at Chang’E-5 landing site in the northern Oceanus Procellarum

2021 ◽  
Author(s):  
Hanjie Song ◽  
Hui Sun ◽  
Gang Yu ◽  
Yang Liu ◽  
Juan Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Lunar Regolith ◽  
Landing Site ◽  
Radar Data ◽  
Detection Methods ◽  
Force Analysis ◽  
Ridge Detection ◽  
Processing Procedure ◽  
Geological Context

Abstract The Lunar Regolith Penetrating Radar (LRPR) on the Chang’E-5 (CE-5) lander was deployed to investigate structures of the regolith. The migration and ridge detection methods were used to process the radar data, and the results indicate a 4.5 m regolith thickness that contains four units at the landing site, which is characterized by different internal reflections that point to their various compositions, mainly comprise protolith and admixed ejecta from the Harpalus, Copernicus, and Aristarchus. High-resolution processing for the LRPR data indicates a few rocks or slates with depth from ~ 0.2 m to over 1 m in the subsurface at the landing site, which was validated by the force analysis during the drilling of the regolith into ~ 1 m depth. The processing procedure proposed in this study is capable of producing reliable and precise images of the lunar regolith substructure, which provides important geological context on the returned drilling samples.

scholarly journals Rock Location and Quantitative Analysis of Regolith at the Chang’e 3 Landing Site Based on Local Similarity Constraint

2019 ◽  
Vol 11 (5) ◽  
pp. 530 ◽  
Author(s):  
Bin Hu ◽  
Deli Wang ◽  
Ling Zhang ◽  
Zhaofa Zeng
Keyword(s):  
Quantitative Analysis ◽  
Lunar Regolith ◽  
Landing Site ◽  
Threshold Function ◽  
Local Similarity ◽  
Near Surface ◽  
Processing Pipeline ◽  
Mode Decomposition ◽  
Lunar Geology ◽  
The One

Structural analysis of lunar regolith not only provides important information about lunar geology but also provides a reference for future lunar sample return missions. The Lunar Penetrating Radar (LPR) onboard China’s Chang’E-3 (CE-3) provides a unique opportunity for mapping the subsurface structure and the near-surface stratigraphic structure of the regolith. The problem of rock positioning and regolith-basement interface highlighting is meaningful. In this paper, we propose an adaptive rock extraction method based on local similarity constraints to achieve the rock location and quantitative analysis for regolith. Firstly, a processing pipeline is designed to image the LPR CH-2 A and B data. Secondly, we adopt an f-x EMD (empirical mode decomposition)-based dip filter to extract low-wavenumber components in the two data. Then, we calculate the local similarity spectrum between the filtered CH-2 A and B. After a soft threshold function, we pick the local maximums in the spectrum as the location of each rock. Finally, according to the extracted result, on the one hand, the depth of regolith is obtained, and on the other hand, the distribution information of the rocks in regolith, which changes with the path and the depth, is also revealed.

scholarly journals A Novel Approach for Permittivity Estimation of Lunar Regolith Using the Lunar Penetrating Radar Onboard Chang’E-4 Rover

2021 ◽  
Vol 13 (18) ◽  
pp. 3679
Author(s):  
Ruigang Wang ◽  
Yan Su ◽  
Chunyu Ding ◽  
Shun Dai ◽  
Chendi Liu ◽  
...  
Keyword(s):  
High Frequency ◽  
Relative Permittivity ◽  
Traditional Method ◽  
Lunar Regolith ◽  
Landing Site ◽  
New Approach ◽  
High Frequency Radar ◽  
Novel Approach ◽  
Fitting Method ◽  
Simulation Results

Accurate relative permittivity is essential to the further analysis of lunar regolith. The traditional hyperbola fitting method for the relative permittivity estimation using the lunar penetrating radar generally ignored the effect of the position and geometry of antennas. This paper proposed a new approach considering the antenna mounting height and spacing in more detail. The proposed method is verified by numerical simulations of the regolith models. Hence the relative permittivity of the lunar regolith is calculated using the latest high-frequency radar image obtained by the Yutu-2 rover within the first 24 lunar days. The simulation results show that the relative permittivity is underestimated when derived by the traditional method, especially at the shallow depth. The proposed method has improved the accuracy of the estimated lunar regolith relative permittivity at a depth of 0–3 m, 3–6 m, and 6–10 m by 35%, 14%, and 9%, respectively. The thickness of the lunar regolith at the Chang’E 4 landing site is reappraised to be 11.1 m, which improved by ~8% compared with previous studies.

scholarly journals Parameter Estimation of Lunar Regolith from Lunar Penetrating Radar Data

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2907 ◽  
Author(s):  
Ling Zhang ◽  
Zhaofa Zeng ◽  
Jing Li ◽  
Ling Huang ◽  
Zhijun Huo ◽  
...  
Keyword(s):  
Dielectric Constant ◽  
Parameter Estimation ◽  
Lunar Regolith ◽  
Relative Dielectric Constant ◽  
Landing Site ◽  
Radar Data ◽  
Titanium Content ◽  
Complex Model ◽  
Electrical Parameters ◽  
Near Surface

Parameter estimation of the lunar regolith not only provides important information about the composition but is also critical to quantifying potential resources for lunar exploration and engineering for human outposts. The Lunar Penetrating Radar (LPR) onboard China’s Chang’E-3 (CE-3) provides a unique opportunity for mapping the near-surface stratigraphic structure and estimating the parameters of the regolith. In this paper, the electrical parameters and the iron-titanium content of regolith are estimated based on the two sets of LPR data. Firstly, it is theoretically verified that the relative dielectric constant can be estimated according to the difference of the reflected time of two receivers from a same target. Secondly, in order to verify the method, a parameter estimation flow is designed. Subsequently, a simple model and a complex model of regolith are carried out for the method verification. Finally, on the basis of the two sets of LPR data, the electrical parameters and the iron-titanium content of regolith are estimated. The relative dielectric constant of regolith at CE-3 landing site is 3.0537 and the content of TiO2 and FeO is 14.0127%. This helps us predict the reserves of resources at the CE-3 landing site and even in the entire Mare Imbrium.

scholarly journals Olivine-norite rock detected by the lunar rover Yutu-2 likely crystallized from the SPA-impact melt pool

2019 ◽  
Vol 7 (5) ◽  
pp. 913-920 ◽  
Author(s):  
Honglei Lin ◽  
Zhiping He ◽  
Wei Yang ◽  
Yangting Lin ◽  
Rui Xu ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Lunar Regolith ◽  
Thermal Conditions ◽  
Landing Site ◽  
Lunar Crust ◽  
Imaging Spectrometer ◽  
Melt Pool ◽  
Moon Mineralogy Mapper ◽  
The Impact

Abstract Chang’E-4 landed in the South Pole-Aitken (SPA) basin, providing a unique chance to probe the composition of the lunar interior. Its landing site is located on ejecta strips in Von Kármán crater that possibly originate from the neighboring Finsen crater. A surface rock and the lunar regolith at 10 sites along the rover Yutu-2 track were measured by the onboard Visible and Near-Infrared Imaging Spectrometer in the first three lunar days of mission operations. In situ spectra of the regolith have peak band positions at 1 and 2 μm, similar to the spectral data of Finsen ejecta from the Moon Mineralogy Mapper, which confirms that the regolith's composition of the landing area is mostly similar to that of Finsen ejecta. The rock spectrum shows similar band peak positions, but stronger absorptions, suggesting relatively fresh exposure. The rock may consist of 38.1 ± 5.4% low-Ca pyroxene, 13.9 ± 5.1% olivine and 48.0 ± 3.1% plagioclase, referred to as olivine-norite. The plagioclase-abundant and olivine-poor modal composition of the rock is inconsistent with the origin of the mantle, but representative of the lunar lower crust. Alternatively, the rock crystallized from the impact-derived melt pool formed by the SPA-impact event via mixing the lunar crust and mantle materials. This scenario is consistent with fast-cooling thermal conditions of a shallow melt pool, indicated by the fine to medium-sized texture (<3 mm) of the rock and the SPA-impact melting model [Icarus 2012; 220: 730–43].

scholarly journals A Compressive Sensing-Based Approach to Reconstructing Regolith Structure from Lunar Penetrating Radar Data at the Chang’E-3 Landing Site

2018 ◽  
Vol 10 (12) ◽  
pp. 1925 ◽  
Author(s):  
Kun Wang ◽  
Zhaofa Zeng ◽  
Ling Zhang ◽  
Shugao Xia ◽  
Jing Li
Keyword(s):  
Fourier Series ◽  
Compressive Sensing ◽  
Time Delays ◽  
Lunar Regolith ◽  
Landing Site ◽  
Radar Data ◽  
Lunar Rover ◽  
Signal Parameters ◽  
Lunar Environment ◽  
Scientific Systems

Lunar Penetrating Radar (LPR) is one of the important scientific systems onboard the Yutu lunar rover for the purpose of detecting the lunar regolith and the subsurface geologic structures of the lunar regolith, providing the opportunity to map the subsurface structure and vertical distribution of the lunar regolith with a high resolution. In this paper, in order to improve the capability of identifying response signals caused by discrete reflectors (such as meteorites, basalt debris, etc.) beneath the lunar surface, we propose a compressive sensing (CS)-based approach to estimate the amplitudes and time delays of the radar signals from LPR data. In this approach, the total-variation (TV) norm was used to estimate the signal parameters by a set of Fourier series coefficients. For this, we chose a nonconsecutive and random set of Fourier series coefficients to increase the resolution of the underlying target signal. After a numerical analysis of the performance of the CS algorithm, a complicated numerical example using a 2D lunar regolith model with clipped Gaussian random permittivity was established to verify the validity of the CS algorithm for LPR data. Finally, the compressive sensing-based approach was applied to process 500-MHz LPR data and reconstruct the target signal’s amplitudes and time delays. In the resulting image, it is clear that the CS-based approach can improve the identification of the target’s response signal in a complex lunar environment.

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