Convolutional Models for Landmine Identification with Ground Penetrating Radar

Convolutional Models for Landmine Identification with Ground Penetrating Radar
Author: Friedrich Roth
Publisher: Delft University Press
Total Pages: 174
Release: 2004-01-01
Genre: Science
ISBN: 9789040725685
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This is a Ph.D. dissertation. Contents include: The global landmine problem, Current demining techniques, Ground penetrating radar (GPR) for landmine detection and identification, The GPR response of a landmine and its use for target identification, Scope of the research, Thesis outline, Scattering from a homogeneous minelike target, Convolutional models for backscattering from a buried minelike target, deconvolutional and target characterization, 3D finite-difference time-domain (FDTD) simulation results and verification, Host medium transformation of the response of a dielectric minelike target, Scattering from a minelike target with internal structure, Convolutional models for backscattering from a buried dielectric minelike target with internal structure Deconvolution and target characterization, 3D finite-difference time-domain (FDTD) simulation results and verification, GPR landmine identification, GPR hardware, Convolutional GPR models, preprocessing, Deconvolution and target characterization, Experimental results and validation, Data acquisition, Data analysis, Overview of the research results and recommendations.

Linear Prediction Models for Landmine Detection Using Handheld Ground Penetrating Radar

Linear Prediction Models for Landmine Detection Using Handheld Ground Penetrating Radar
Author: Kunal M. Raval
Publisher:
Total Pages: 176
Release: 2004
Genre: Land mines
ISBN:
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The detection of land mine using Ground Penetrating Radar (GPR) is very difficult task because the back ground clutter characteristics are non-stationary and land mine signatures are inconsistent. Continuing the work of Dr. Ho and Dr. Gader, the aim in this research is to reduce the false alarm rate further by taking into account data from both front and back antenna simultaneously. Four new Linear Prediction models have been proposed to model the clutter vector sample. The detector first computes the Maximum Likelihood Estimate of the prediction coefficients which in turn used to generate the prediction error. The linear prediction coefficients are made adaptive to take into account the time-varying behavior of background clutter. If the prediction error is larger than the preset adaptive threshold, the detector decides the current vector sample is from landmine. Otherwise the current vector sample is from clutter. Furthermore, linear prediction has been done in several frequency subbands to take into account the distinct reflection characteristics of landmines at different frequencies to improve the detection accuracy. The same procedure has been repeated for the current vector sample from the back antenna.

Advanced Feature Based Techniques for Landmine Detection Using Ground Penetrating Radar

Advanced Feature Based Techniques for Landmine Detection Using Ground Penetrating Radar
Author: Zhenhua Ma
Publisher:
Total Pages:
Release: 2007
Genre: Electronic dissertations
ISBN:
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Land mine detection is an important and yet challenging problem that remains to be solved. It is not only a problem for military, but also for humanitarian concern. The goal of this research is to propose some techniques for landmine detection. Two advanced feature based techniques are developed. One algorithm applies the clustering method based on the spectral feature vectors formed by the energy density spectra of return sensor signals, the idea behind is to find out whether there are some "hidden patterns" among the spectral feature vectors. The other one is the subspace detector technique that utilizes the energy density spectra of return signals directly. These techniques are tested in various testing data sets collected from the vehicle mounted ground penetrating radar to evaluate their ability to improve the detection result and reduce the false alarm rates. Both of them are proved to be useful in improving the detection of land mines.

Online Dictionary Learning for Classification of Antipersonnel Landmines Using Ground Penetrating Radar

Online Dictionary Learning for Classification of Antipersonnel Landmines Using Ground Penetrating Radar
Author: Fabio Giovanneschi
Publisher: Fraunhofer Verlag
Total Pages: 134
Release: 2021-05-03
Genre:
ISBN: 9783839616758
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Ground penetrating radar (GPR) target detection and classification is a challenging task. Here, online dictionary learning (DL) methods are considered to obtain sparse representations (SR) of the GPR data to enhance feature extraction for target classification via support vector machines. Online methods are preferred because traditional batch DL algorithms are not scalable to high-dimensional data. A Drop-Off MINi-batch Online Dictionary Learning (DOMINODL) method, which exploits the fact that a lot of the training data may be correlated, is also developed. For the case of abandoned anti-personnel landmines classification, the performance of K-SVD is compared with three online algorithms: classical Online Dictionary Learning, its correlation-based variant and DOMINODL. Experiments with real data from L-band GPR show that online DL methods reduce learning time by 36-93% and increase mine detection by 4-28% over K-SVD. DOMINODL is the fastest and retains similar classification performance as the other approaches. For the selection of optimal DL input parameters, the Kolmogorov-Smirnoff test distance and the Dvoretzky-Kiefer-Wolfowitz inequality are used.

Ground Penetrating Radar Theory and Applications

Ground Penetrating Radar Theory and Applications
Author: Harry M. Jol
Publisher: Elsevier
Total Pages: 545
Release: 2008-12-08
Genre: Science
ISBN: 0080951848
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Ground-penetrating radar (GPR) is a rapidly developing field that has seen tremendous progress over the past 15 years. The development of GPR spans aspects of geophysical science, technology, and a wide range of scientific and engineering applications. It is the breadth of applications that has made GPR such a valuable tool in the geophysical consulting and geotechnical engineering industries, has lead to its rapid development, and inspired new areas of research in academia. The topic of GPR has gone from not even being mentioned in geophysical texts ten years ago to being the focus of hundreds of research papers and special issues of journals dedicated to the topic. The explosion of primary literature devoted to GPR technology, theory and applications, has lead to a strong demand for an up-to-date synthesis and overview of this rapidly developing field. Because there are specifics in the utilization of GPR for different applications, a review of the current state of development of the applications along with the fundamental theory is required. This book will provide sufficient detail to allow both practitioners and newcomers to the area of GPR to use it as a handbook and primary research reference. *Review of GPR theory and applications by leaders in the field*Up-to-date information and references*Effective handbook and primary research reference for both experienced practitioners and newcomers