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The Lunar Penetrating Radar (LPR) is one of the important scientific payloads in China’s Chang’E-3 (CE-3) to image within 100 m below the lunar surface. The acquired LPR data is significant for the research of lunar geological structure. Based on the sedimentary mechanism of lunar regolith, the regolith contains many rocks with different sizes. These local anomalies appear as diffraction in LPR data, which reduces the data quality and limits the structural analysis of lunar regolith. According to the kinematics characteristics of rock caused diffraction, we transform these problems to a problem of steep dip decreasing. To reach this goal, we adopt a data preprocessing workflow to improve the quality of the radar image, firstly. Then, a dip filter based on adaptive f-x empirical mode decomposition (EMD) is proposed to extract the rocks in the regolith and the corresponding removed IMF map indicates the degree of rock enrichment and highlights regolith-basement interface. Both simulation and LPR CH-2 data present a great performance. Finally, according to the processed result, we locate the position of each rock and highlight the contact interface of regolith and the basement rock.

Structural Analysis of Lunar Regolith from LPR CH-2 Data Based on Adaptive f-x E MD: LPR Data Processed by Adaptive f-x EMD