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Keywords = TKEO-slices

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13 pages, 18243 KB  
Technical Note
The LPR Instantaneous Centroid Frequency Attribute Based on the 1D Higher-Order Differential Energy Operator
by Xuebing Zhang, Zhengchun Song, Bonan Li, Xuan Feng, Jiangang Zhou, Yipeng Yu and Xin Hu
Remote Sens. 2023, 15(22), 5305; https://doi.org/10.3390/rs15225305 - 9 Nov 2023
Cited by 2 | Viewed by 1797
Abstract
In ground-penetrating radar (GPR) or lunar-penetrating radar (LPR) interpretation, instantaneous attributes (e.g., instantaneous energy and instantaneous frequency) are often utilized for attribute analysis, and they can also be integrated into a new attribute, i.e., the instantaneous centroid frequency. Traditionally, the estimation of instantaneous [...] Read more.
In ground-penetrating radar (GPR) or lunar-penetrating radar (LPR) interpretation, instantaneous attributes (e.g., instantaneous energy and instantaneous frequency) are often utilized for attribute analysis, and they can also be integrated into a new attribute, i.e., the instantaneous centroid frequency. Traditionally, the estimation of instantaneous attributes calls for complex trace analysis or energy operator schemes (e.g., the Teager–Kaiser energy operator, TKEO). In this work, we introduce the 1D higher-order differential energy operator (1D-HODEO) to track instantaneous attributes with better localization. In collocation with the mode decomposition algorithms, the 1D-HODEO performs along each A-scan on the decomposed mode slices to form the final profile of instantaneous centroid frequency by using the piece-wise correlation coefficients. Both a numerical model for simulating two-layer lunar regolith and the LPR Yutu-2 data show that the proposed instantaneous centroid frequency profile on the 1D-HODEO has better resolution, in comparison with that of TKEO and the traditional time-varying centroid frequency. In this work, we present a new approach for extracting instantaneous centroid frequency attributes which provides more comprehensive information in lunar stratigraphic interpretation and LPR attribute analysis. Full article
(This article belongs to the Special Issue Ground Penetrating Radar (GPR) Applications in Earth, Moon and Planetary Exploration)
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15 pages, 16055 KB  
Technical Note
GPR Energy Attribute Slices Based on Multivariate Variational Mode Decomposition and Teager–Kaiser Energy Operator
by Xuebing Zhang, Yuxiang Qin, Zhengkun Hu, Xin Hu, Xuan Feng and Yuan Chai
Remote Sens. 2022, 14(19), 4805; https://doi.org/10.3390/rs14194805 - 26 Sep 2022
Cited by 6 | Viewed by 2342
Abstract
The GPR signals appear nonlinear and nonstationary during propagation. To evaluate the nonstationarity, the empirical mode decomposition (EMD) and its modifications have been proposed to localize the variations of energy and frequency components over time. Among the EMD−based algorithms, the variational mode decomposition [...] Read more.
The GPR signals appear nonlinear and nonstationary during propagation. To evaluate the nonstationarity, the empirical mode decomposition (EMD) and its modifications have been proposed to localize the variations of energy and frequency components over time. Among the EMD−based algorithms, the variational mode decomposition (VMD) is one of the representative methods. It eliminates the drawbacks of EMD, to some extent, but is still executed in one dimension. In this work, the multivariate variational mode decomposition (MVMD) algorithm is introduced for decomposing the GPR B-scans into several IMF-slices in two dimensions, which inherits the advantages of the VMD and considers the stratigraphic constraints. Then, by applying the Teager–Kaiser energy operator (TKEO) within each IMF-slice, a novel energy attribute is formed and termed as the “TKEO-slices”. The proposed TKEO-slices can localize the energy attribute of geophysical information of different scales with good stratigraphic continuity. The proposed scheme is evaluated by the synthetic benchmark, model data, and field data. Compared with the VMD−based scheme and the classic instantaneous amplitude, the proposed TKEO-slices show better resolution and lateral continuity. Full article
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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