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Enhanced electromagnetic wave propagation in lossy media
Full text linkLa profondità di penetrazione di onde elettromagnetiche in mezzi con perdita è un parametro fondamentale in molte applicazioni: dall’interazione con tessuti biologici, al GeoRadar (GPR), dalla comunicazione con mezzi sottomarini, all’analisi dei materiali. Questa dissertazione propone un metodo per raggiungere penetrazione profonda in mezzi con perdite attraverso l’uso di una particolare categoria di onde elettromagnetiche, dette inomogenee o non-uniformi. In particolare, viene studiato il comportamento di onde non omogenee all’interfaccia tra due mezzi, il primo, in cui è presente l’onda incidente, privo di perdite, e il secondo, in cui è presente l’onda trasmessa, con perdite. Le “consuete” onde elettromagnetiche omogenee, in questa situazione, provocano un’onda trasmessa che si attenua esponenzialmente nella direzione normale all’interfaccia tra i due mezzi, minimizzando la penetrazione. Al contrario, onde non omogenee possono provocare onde trasmesse che attenuano esponenzialmente, ma in direzioni diverse da quella normale all’interfaccia tra
i due mezzi, per esempio tale direzione può essere parallela all’interfaccia con il mezzo con perdite oppure, il vettore di attenuazione può addirittura presentare un angolo superiore ai novanta gradi con la normale a tale superficie di separazione,
risultando in un’amplificazione del segnale piuttosto che attenuazione nel mezzo con perdite. Si parte con un approccio analitico al problema, seguito poi un approccio numerico di design di antenna
Antenne planari altamente direttive per investigazioni in spazio aperto e in scenari extraterrestri
No full textDeep penetration properties of inhomogeneous waves
No full textThis article demonstrates that high penetration on lossy media can be achieved
by using inhomogeneous waves. Penetration properties of inhomogeneous
waves are initially presented studying a plane wave impinging on the
separation surface between two media, where at least the medium in which the
wave is transmitted is assumed lossy. The theory presented in the first part of
the article is then explored by considering more realistic scenarios based on
leaky waves generated by uniform microstrip antennas in the X band. Finally,
practical limits and potentialities of the shown approach are discussed
Inhomogeneous wave penetration in lossy media
No full textThe penetration properties of inhomogeneous waves are illustrated. A theoretical approach is presented and a leaky-wave antenna design is proposed in order to verify the theoretical implications. Practical aspects related to the excitation of leaky waves able to give rise to deep penetration effects in lossy media are discussed and the possible implementation issues are commente
F. Ponti, F. Barbuto, P. P. Di Gregorio, F. Mangini, P. Simeoni, M. Troiano, F. Frezza, “Deep Learning for analysis of GPR images”, Radar and Remote Sensing Workshop (RRSW) 2019, Roma, 30-31 maggio 2019.
No full textThe aim of this work is to exploit Machine Learning (ML) for the analysis of Georadar (or Ground Penetrating Radar, GPR) images. In particular, the objective is to apply a Deep Learning (DL) architecture to extract from B-scan images of infinite buried Perfect Electric Conductor (PEC) cylinders: the cylinder radius, the depth with respect to the ground, and the relative dielectric permittivity εr of the medium in which the cylinder is immersed. The architecture chosen is the DenseNet. The main feature of this network is that each layer is connected to all subsequent layers, through the concatenation of the feature maps. Indeed, traditional convolutional networks, composed of L layers, present L connections, one for each layer, while DenseNet presents L(L+1)/2 direct connections. The DenseNet network has many advantages: it reduces the problem of the evanescent gradient, strengthens the propagation of features, encourages the reuse of parameters and substantially reduces the number of parameters. The GPR images are obtained through the GprMax software simulation tool, combining the radius and depth of the cylinder, and the relative permittivity of the medium. The network is trained to extract 19 labels opportunely selected from the images (Table 1):
Table 1: Labels.
radius [cm] 1 2 3 4 5
depth [cm] 9 10 11 12 13 14 15
εr (relative dielectric permittivity) 2 3 4 5 6 7 8
The input images, of initial size 3453×1772 pixels, are resized to 32×32 pixels, in order to speed up the training phase. For the purpose of extracting the features of the images, multi-label classification is used. Since the data set is small, the k-fold cross validation is performed by dividing the data set into 10 parts. Therefore 10% of the data constitutes the validation set and the remaining part is chosen as training set. The training of the network is performed by varying opportunely the learning rate.
The study has shown interesting results in terms of the ability of the DenseNet in classifying B-scan images, despite a small data set
Design and realization of a cheap GPR prototype & Recent advancements in forward-scattering methods
No full text
An analytical study of electromagnetic deep penetration conditions and implications in lossy media through inhomogeneous waves
No full textThis paper illustrates how the penetration of electromagnetic waves in lossy media strongly depends on the waveform and not only on the media involved. In particular, the so-called inhomogeneous plane waves are compared against homogeneous plane waves illustrating how the first ones can generate deep penetration effects. Moreover, the paper provides examples showing how such waves may be practically generated. The approach taken here is analytical and it concentrates on the deep penetration conditions obtained by means of incident inhomogeneous plane waves incoming from a lossless medium and impinging on a lossy medium. Both conditions and constraints that the waveforms need to possess to achieve deep penetration are analysed. Some results are finally validated through numerical computations. The theory presented here is of interest in view of a practical implementation of the deep penetration effect
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