High-Resolution Anisotropic Prestack Kirchhoff Dynamic Focused Beam Migration

Sun, Hui; Gao, Cheng; Zhang, Zhihou; Liao, Xiaolong; Xu-yu, Wang; Yang, Jianwen

doi:10.1109/jsen.2019.2933200

Cited by 43 publications

(10 citation statements)

References 48 publications

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“…One possible reason is that the flat diffraction hyperbola would influence the accuracy of semblance analysis. Thus, a high-precision semblance analysis method such as the weighted AB semblance [30] or new migration methods [31] should be developed to improve the accuracy in the future studies. Additionally, LPR data processing should consider the local attributes to separate the data with higher accuracies.…”

Section: Discussionmentioning

confidence: 99%

Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

Song

Zhang

et al. 2020

Remote Sensing

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The Lunar Penetrating Radar (LPR) onboard the Yutu-2 rover from China’s Chang’E-4 (CE-4) mission is used to probe the subsurface structure and the near-surface stratigraphic structure of the lunar regolith on the farside of the Moon. Structural analysis of regolith could provide abundant information on the formation and evolution of the Moon, in which the rock location and property analysis are the key procedures during the interpretation of LPR data. The subsurface velocity of electromagnetic waves is a vital parameter for stratigraphic division, rock location estimates, and calculating the rock properties in the interpretation of LPR data. In this paper, we propose a procedure that combines the regolith rock extraction technique based on local correlation between the two sets of LPR high-frequency channel data and the common offset semblance analysis to determine the velocity from LPR diffraction hyperbola. We consider the heterogeneity of the regolith and derive the relative permittivity distribution based on the rock extraction and semblance analysis. The numerical simulation results show that the procedure is able to obtain the high-precision position and properties of the rock. Furthermore, we apply this procedure to CE-4 LPR data and obtain preferable estimations of the rock locations and the properties of the lunar subsurface regolith.

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Section: Discussionmentioning

confidence: 99%

Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

Song

Zhang

et al. 2020

Remote Sensing

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“…In this process, the local registration algorithm uses the registration algorithm based on improved normal distribution transform, which is our previous research method [ 15 ]. And the global registration uses an automatic multiscan registration algorithm, which is also our previous research method [ 16 , 17 ]. The fusion result of point cloud is shown in Figure 7 .…”

Section: Methodsmentioning

confidence: 99%

Detection of Changes of Ancient Buildings from Terrestrial Laser Scanning and Hyperspectral Imaging

Zhang

Gao

2021

Scanning

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Ancient buildings have various geometric and material changes caused by the historical and natural factors, and their comprehensive detection has also been a more important challenge. This way, in this paper, a flexible, scientific approach from terrestrial laser scanning and hyperspectral imaging is provided for this issue. It is possible to flexibly and accurately detect some potential crisis, which cannot be found in some surface phenomena of historical buildings. Furthermore, one of the main characteristic of this method is that the time and place of the two data acquisition need not be limited, but they can be accurately fused. Another one of the main features is that the fusion data can synthetically detect geometric and material changes of historical buildings. This method was applied to the case study of the Beijing Tianningsi Tower, an extremely dazzling pearl of the Chinese Buddhist pagoda, on which the signs of deformation and restoration were found in the tower shape and in the tower-body sculpture. It was possible to assess the typical physical, chemical, and biological changes of historical buildings, to provide scientific basis for comprehensive research. The results demonstrate that this method is feasible and applicable for detecting changes of ancient buildings and is applied to similar research using more analytical methods for multisource data.

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“…Empirical mode decomposition (EMD) [1] is a local, datadriven, and adaptive method in processing nonlinear and nonstationary signals and has been widely used in machinery, voice, geography, medicine, and other fields [2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

An Improved Empirical Mode Decomposition Based on Local Integral Mean and Its Application in Signal Processing

Xiao-dong

Wang

et al. 2021

Mathematical Problems in Engineering

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Empirical mode decomposition (EMD) is an effective method to deal with nonlinear nonstationary data, but the lack of orthogonal decomposition theory and mode-mixing are the main problems that limit the application of EMD. In order to solve these two problems, we propose an improved method of EMD. The most important part of this improved method is to change the mean value by envelopes of signal in EMD to the mean value by the definite integral, which enables the mean value to be mathematically expressed strictly. Firstly, we prove that the signal is orthogonally decomposed by the improved method. Secondly, the Monte Carlo method of white noise is used to explain that the improved method can effectively alleviate mode-mixing. In addition, the improved method is adaptive and does not need any input parameters, and the intrinsic mode functions (IMFs) generated from it is robust to sifting. We have carried out experiments on a series of artificial and real data, the results show that the improved method is the orthogonal decomposition method and can effectively alleviate mode-mixing, and it has better decomposition performance and physical meaning than EMD, ensemble EMD (EEMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). In addition, the improved method is generally more time-consuming than EMD, but far less than EEMD and CEEMDAN.

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High-Resolution Anisotropic Prestack Kirchhoff Dynamic Focused Beam Migration

Cited by 43 publications

References 48 publications

Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

Detection of Changes of Ancient Buildings from Terrestrial Laser Scanning and Hyperspectral Imaging

An Improved Empirical Mode Decomposition Based on Local Integral Mean and Its Application in Signal Processing

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