As one of the important scientific instruments of lunar exploration, the Lunar Penetrating\nRadar (LPR) onboard Chinaâ??s Changâ??E-3 (CE-3) provides a unique opportunity to image the lunar\nsubsurface structure. Due to the low-frequency and high-frequency noises of the data, only a few\ngeological structures are visible. In order to better improve the resolution of the data, band-pass\nfiltering and empirical mode decomposition filtering (EMD) methods are usually used, but in\nthis paper, we present a mathematical morphological filtering (MMF) method to reduce the noise.\nThe MMF method uses two structural elements with different scales to extract certain scale-range\ninformation from the original signal, at the same time, the noise beyond the scale range of the two\ndifferent structural elements is suppressed. The application on synthetic signals demonstrates that\nthe morphological filtering method has a better performance in noise suppression compared with\nband-pass filtering and EMD methods. Then, we apply band-pass filtering, EMD, and MMF methods\nto the LPR data, and the MMF method also achieves a better result. Furthermore, according to the\nresult by MMF method, three stratigraphic zones are revealed along the roverâ??s route.
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