NOISE REDUCTION AND INTERPRETATION OF ICE-PENETRATING RADAR DATA IN ANTARCTIC ICE SHEET BASED ON VARIATIONAL MODE DECOMPOSITION

Abstract. Ice-penetrating radar is an effective method for studying the subglacial bedrock and ice information within the Antarctic ice sheet. Because of the low conductivity of ice and the relatively uniform composition of ice sheets in the polar region, ice-penetrating radar can penetrate deeper part of the ice sheet and collect the following data. However, it is still necessary to suppress the noise from radar data to obtain more accurate and effective data. In this paper, the entirely non-recursive Variational Mode Decomposition (VMD) is applied to the data noise reduction of ice-penetrating radar data. VMD is a decomposition method of adaptive and quasi-orthogonal signals, which decomposes airborne radar data into multiple frequency-limited quasi-orthogonal Intrinsic Mode Functions (IMFs). The IMFs containing noise are then removed according to the information distribution in the IMFs component and the remaining IMFs are reconstructed. We implements the method to process the real ice-penetrating radar data, which effectively eliminates the interference noise in the data, improves the signal-to-noise ratio and characterizes the internal layer structure of ice. It is verified that the method can be applied to the noise reduction processing of polar ice-penetrating radar data successful, which provides a better basis for data interpretation. Finally, we present the internal structure within the ice sheet based on VMD denoised radar profile.