Abstract

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.

Highlights

  • IntroductionOn 3 January 2019, China’s Chang’E-4 spacecraft successfully landed in the Von Karmen crater within the South Pole-Aitken basin (SPA) on the far side of the Moon [2]

  • The airless Moon is the closest extraterrestrial object to the Earth

  • We calculated the relative permittivity by the traditional hyperbola fitting method and the new method and compared the estimated value with the real value set in the simulation model

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Summary

Introduction

On 3 January 2019, China’s Chang’E-4 spacecraft successfully landed in the Von Karmen crater within the South Pole-Aitken basin (SPA) on the far side of the Moon [2]. It is the first in situ exploration for human beings on the far side of the Moon, which is conducive to unveiling the mystery of the lunar subsurface structures [3]. There are three methods to estimate the relative permittivity of the lunar materials: laboratory sample measurement, remote sensing, and in situ detection [6,7,8,9,10,11].

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