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Pregled bibliografske jedinice broj: 993286

Detection of low-metallic content landmines based on electromagnetic induction model


Ambruš, Davorin
Detection of low-metallic content landmines based on electromagnetic induction model, 2019., doktorska disertacija, Fakultet elektrotehnike i računarstva, Zagreb


CROSBI ID: 993286 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Detection of low-metallic content landmines based on electromagnetic induction model
(Otkrivanje mina s malom količinom metala zasnovano na elektromagnetskom induktivnom modelu)

Autori
Ambruš, Davorin

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, doktorska disertacija

Fakultet
Fakultet elektrotehnike i računarstva

Mjesto
Zagreb

Datum
02.04

Godina
2019

Stranica
312

Mentor
Bilas, Vedran

Ključne riječi
metal detection, metal characterization, electromagnetic induction, induced magnetic dipole, magnetic polarizability tensor, nonlinear least squares, magnetic tracking

Sažetak
Antipersonnel landmines are a global safety hazard that indiscriminately affects both soldiers and civilians, causing severe injuries and deaths years after the cessation of conflicts. This thesis presents an attempt to improve the existing methods of close-in detection of landmines, particularly those with low metallic content, using electromagnetic induction (EMI) sensing. A key assumption is that such improvement could be obtained by shifting from an existing concept of metal detection to a concept of metallic target characterization. This could ultimately lead to safer, faster and cheaper humanitarian demining. The landmine problem and the concept of humanitarian mine action are introduced first. State-of-the art methods of close-in landmine detection are briefly described, with an emphasis on metal detection as a key sensing modality. An analytical forward model of a scanning EMI sensor for metallic target characterization, based on the induced magnetic dipole mode, is devised from the governing EMI equations. Several representative search head designs are selected, which will be used throughout the thesis for conceptual tests. Three different static inversion methods for the estimation of induced dipole model parameters from EMI and sensor positional data are analyzed ; the method based on nonlinear least squares (NLS) approach, the quasi-numerical HAP method featuring the modified NSMS model, and the metaheuristic method. Inversion performance of each method is evaluated on a synthetic data set, for selected metallic targets and representative search head geometries. A novel approach to tracking of the search head's pose based on the measurement of its own primary magnetic field and the application of the extended Kalman filter is presented. Following a similar methodology based on Bayesian filtering, a new concept of dynamic dipole inversion that avoids the need for sensor positional data is proposed. The effects of background interferences on a response of an EMI sensor for use in humanitarian demining and the methods for their compensation are also analyzed. A novel concept for robust estimation of target's shape, based on temporal information stored in the eigenvalues of the estimated magnetic polarizability tensor, is introduced. Finally, all the presented modeling, inversion, tracking and compensation approaches are experimentally validated on several sensing platforms in a laboratory and field environment.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Vedran Bilas (mentor)

Avatar Url Davorin Ambruš (autor)


Citiraj ovu publikaciju

Ambruš, Davorin
Detection of low-metallic content landmines based on electromagnetic induction model, 2019., doktorska disertacija, Fakultet elektrotehnike i računarstva, Zagreb
Ambruš, D. (2019) 'Detection of low-metallic content landmines based on electromagnetic induction model', doktorska disertacija, Fakultet elektrotehnike i računarstva, Zagreb.
@phdthesis{phdthesis, author = {Ambru\v{s}, D.}, year = {2019}, pages = {312}, keywords = {metal detection, metal characterization, electromagnetic induction, induced magnetic dipole, magnetic polarizability tensor, nonlinear least squares, magnetic tracking}, title = {Detection of low-metallic content landmines based on electromagnetic induction model}, keyword = {metal detection, metal characterization, electromagnetic induction, induced magnetic dipole, magnetic polarizability tensor, nonlinear least squares, magnetic tracking}, publisherplace = {Zagreb} }
@phdthesis{phdthesis, author = {Ambru\v{s}, D.}, year = {2019}, pages = {312}, keywords = {metal detection, metal characterization, electromagnetic induction, induced magnetic dipole, magnetic polarizability tensor, nonlinear least squares, magnetic tracking}, title = {Otkrivanje mina s malom koli\v{c}inom metala zasnovano na elektromagnetskom induktivnom modelu}, keyword = {metal detection, metal characterization, electromagnetic induction, induced magnetic dipole, magnetic polarizability tensor, nonlinear least squares, magnetic tracking}, publisherplace = {Zagreb} }




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