scholarly journals Modeling Buried Object Brightness and Visibility for Ground Penetrating Radar

2021 ◽  
pp. 1-15
Author(s):  
Garrett A. Stevenson ◽  
Jason Wilson ◽  
Brian M. Worthmann ◽  
Wlamir Xavier
Keyword(s):  
Ground Penetrating Radar ◽  
Buried Object ◽  
Ground Penetrating

scholarly journals GPR Signal Processing with Geography Adaptive Scanning using Vector Radar for Antipersonal Landmine Detection

10.5772/5696 ◽  
2007 ◽  
Vol 4 (2) ◽  
pp. 22 ◽  
Author(s):  
Toshio Fukuda ◽  
Yasuhisa Hasegawa ◽  
Yasuhiro Kawai ◽  
Shinsuke Sato ◽  
Zakarya Zyada ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Ground Surface ◽  
Landmine Detection ◽  
Image Objects ◽  
Kirchhoff Migration ◽  
Surface Image ◽  
Buried Object ◽  
Ground Penetrating ◽  
The Relationship ◽  
Object Imaging

Ground Penetrating Radar (GPR) is a promising sensor for landmine detection, however there are two major problems to overcome. One is the rough ground surface. The other problem is the distance between the antennas of GPR. It remains irremovable clutters on a sub-surface image output from GPR by first problem. Geography adaptive scanning is useful to image objects beneath rough ground surface. Second problem makes larger the nonlinearity of the relationship between the time for propagation and the depth of a buried object, imaging the small objects such as an antipersonnel landmine closer to the antennas. In this paper, we modify Kirchhoff migration so as to account for not only the variation of position of the sensor head, but also the antennas alignment of the vector radar. The validity of this method is discussed through application to the signals acquired in experiments.

Buried Object Characterization Using Ultra-Wideband Ground Penetrating Radar

2012 ◽  
Vol 60 (8) ◽  
pp. 2654-2664 ◽  
Author(s):  
Lin Li ◽  
Adrian Eng-Choon Tan ◽  
Kashish Jhamb ◽  
Karumudi Rambabu
Keyword(s):  
Ground Penetrating Radar ◽  
Ultra Wideband ◽  
Buried Object ◽  
Ground Penetrating

scholarly journals GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 132
Author(s):  
Roger Tilley ◽  
Hamid Sadjadpour ◽  
Farid Dowla
Keyword(s):  
Comparative Study ◽  
Excitation Function ◽  
Ground Penetrating Radar ◽  
Expectation Maximization ◽  
Gaussian Mixture ◽  
Excitation Pulse ◽  
Buried Objects ◽  
Em Method ◽  
Buried Object ◽  
Ground Penetrating

Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.

scholarly journals Underground Object Size Approximation using GPR Signal and Image Processing

2020 ◽  
Vol 9 (7) ◽  
pp. 1238-1242
Keyword(s):  
Image Processing ◽  
Ground Penetrating Radar ◽  
Region Of Interest ◽  
Dual Approach ◽  
Buried Objects ◽  
Data Application ◽  
Buried Object ◽  
Surface Dimension ◽  
Ground Penetrating

This paper comprises a step wise method of approximating the size of an underground object using GPR (Ground Penetrating Radar). It involves more than just using predefined filters and techniques. Usage of Trivial method of mathematics to calculate the top surface dimensions of the buried objects is the main purpose of this paper. Problem that is faced that, only the presence of any object can be known using the GPR resource, but not exactly how to derive the size of the object using the same data. This method consists of a dual approach to the problem to make sure that the data that is being given out is accurate. The objectives of this paper are to use the GPR to calculate the top surface dimension of a buried object at a suitable depth according to the frequency. The steps that are incorporated include pre-processing of raw data, determination of ROI (Region of interest) from the pre-processed data, Application of appropriate filters for image processing and estimating surface area and depth of the concealed object. The main reason of this paper is to serve the purpose of detecting what is under the ground in a quick and simpler way using the algorithm proposed

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