Conference PaperPDF Available

A Multistatic Uniform Diffraction Tomographic Algorithm for Real-Time Moisture Detection

Authors:

Figures

Content may be subject to copyright.
A Multistatic Uniform Diffraction Tomographic
Algorithm for Real-Time Moisture Detection
Adel Omrani, Guido Link, John Jelonnek∗†
Institute for Pulsed Power and Microwave Technology (IHM)
Institute of Radio Frequency Engineering and Electronics (IHE)
Karlsruhe Institute of Technology, Karlsruhe, Germany
Email: adel.hamzekalaei@kit.edu
Abstract—To obtain the moisture distribution inside a polymer
foam after drying in a conveyor belt system in real time, a
Multistatic Uniform Diffraction Tomography (MUDT) imaging
algorithm is proposed. It is estimated that MUDT provides a
better spatial resolution than the original uniform diffraction
tomography (UDT). Additionally, it allows to resolve the distri-
bution of the different scatterers, which is shown by simulation
results.
Index Terms—microwave imaging, tomography, moisture de-
tection
I. INTRODUCTION
Microwave drying is an emerging technology of increasing
interest. It is the preferred method of choice particularly
for polymer foam that has low thermal conductivity. Us-
ing an intelligent control of distributed microwave sources
[1], non-uniform moisture distribution could be much more
efficiently addressed. But, it requires the in-situ and non-
invasive measurements of the unknown moisture distribution
inside the material under test. A novel method for microwave
tomography (MWT) in real time is in preparation for moisture
detection of a polymer foam that will be used in combination
with a HEPHAISTOS microwave system, as shown in Fig. 1a.
This HEPHAISTOS microwave oven has a patented hexag-
onal cross-section [2]. In our specific case, the overall length
and hexagon circumferential diameters of the oven are 4 m
and 1 m, respectively. The oven has a modular structure and
consists of three microwave modules of the same type, each 1
m in length and with six slotted waveguide antennas mounted.
Each of those antennas is fed by a 2 kW magnetron working at
the 2.45 GHz ISM frequency band. The total microwave power
installed in the system is about 36 kW. In addition, a 28 kW
convective heating system is installed to help the removal of
the water vapor out of the microwave-drying chamber. That
avoids the condensing of water on the cold metal walls of the
microwave oven. Another unique feature of the HEPHAISTOS
system is the conveyor belt as shown in Fig. 1, which allows
a continuous production process [3].
In [4] a Through Wall Imaging (TWI) method is proposed
that bases on the Uniform Diffraction Tomography (UDT)
method. The location of an object inside or behind the wall
is determined by the linear relationship between the object
function and the received signal in the spectral domain for the
Fig. 1. Microwave drying system with conveyor-belt.
multilayered media. Using a conveyor belt system complicates
the task to locate an object significantly. Not only the real-
time image reconstruction is important but also the real-time
data acquisition is a critical task. Using only one antenna and
moving the antenna for data acquisition is not applicable in
fast data acquisition so the array of the antennas needs to
be fixed. On the other side, the number of antennas cannot
be too high because, again, it takes time for data collection.
Under those conditions, i.e., 1) the low number of antennas,
and, 2) if two adjacent antennas are not in close vicinity
to each other, the UDT imaging algorithm fails to truly
reconstruct the location of the scatterers. The MUDT proposed
here does overcome this problem. It provides high-resolution
and real-time images through the foam by the same number
of transmitters and employing non-diagonal elements of the
scattering matrix. For simplicity, the algorithm is presented for
a 2-D problem. The paper is organized as follows: in Section
II the MUDT formulation and differences with UDT are
presented. In section III the simulation results are presented.
Concluding remarks are provided in section IV.
II. MULTISTATIC UNIFORM DIFFRACTION
TOMOGRAPHY
A. The Forward Model
The 2-D configuration of the multistatic microwave imaging
system is illustrated in Fig. 2. The array of antennas is located
in semi-infinite free space and above the polymer foam with
variations of dielectric properties in the z-direction only. The
distance of the antenna from the top of the polymer foam is t1.
t2is the thickness of the polymer foam with the permittivity
2.
The Lippmann-Schwinger integral equation of the EM scat-
tering problem shown in Fig. 2, can be written in the following
form [5], [6]:
(1)
~
Esct
n(~rr, ~rt) = ~
Etot
n(~rr, ~rt)~
Einc(~rr, ~rt)
=k2Z
d~r 0¯
¯
G(n1)(~rr, ~r0)·O(~r0)~
Etot
n(~r0)
where ~
Etot
nis the total electric field in layer n(n= 1,2,3),
~
Esct
nrepresents the scattered field due to the unknown irreg-
ularities in layer n, while ~
Einc denotes the incident electric
field. O(~r 0) = (ˆ(~r 0)b) is the object function. ˆ(~r 0)is
the profile of the permittivity of the target and bdenotes
the permittivity of the background. Here, a time harmonic
field is assumed. Hence, the complex time harmonic function
ejωt can be eliminated from the equation. ωis the angular
frequency. In (1), the vectors ~rr= (yr, zr)and ~rt= (yt, zt)
represent observation and source points while ¯
¯
G(n1)(~rr, ~rt)
is the background (multilayered media without any scatterer
inside) dyadic Green’s function (DGF). The superscript (n1)
denotes that the source point is located in layer 1and the
observation point is in layer n.
Under the first-order Born approximation the total electric field
~
Etot
ncan be replaced by the background electric field of the
layer and due to the excitation by a line source the electric
field can be replaced by the Green’s function and also using
the symmetry property of Green’s function. Equation 1can be
expressed as stated in [5], [7]
~
Esct
n(~rr, ~rt) = k2Z
d~r 0¯
¯
G(n1)(~rr, ~r 0)·O(~r 0)¯
¯
G(n1)(~r 0, ~rr)
(2)
Furthermore, for writing the background Green’s function in
layer n, the contrast between the layers is assumed to be
small and the reflected wave from the layers is suppressed. So,
the Green’s function is modeled by the incident field in that
layer. If the contrast for the permittivity between the different
layers is sufficiently large, this assumption leads to a late-time
shadow image in the layer.
The spectral representation of the Green’s function in the nth
layer when the line source is located in region 1is [6], [8]
(3)
¯
¯
G(n1)(~r , ~rt)
=1
πZ+
−∞
˜
Tn(ky, kz)ejkzn (zzt)
kz1
ejky(yyt)dky
If z > ztand =(k2
nk2
y)1/2<0.˜
T(ky, kz) is the transmission
coefficient in the nth layer and can be obtained by applying
the boundary conditions between layers for the transverse
magnetic field in x-direction (TMx) [6]. The dispersion re-
lation in the layer lis expressed by kzl =qk2
lk2
yl and
Fig. 2. The antenna array is located above a polymer foam. The first and last
media are half space.
kl=k0lis the wavenumber in layer lwhile k0is the free-
space wavenumber.
The above representation of the scattered field, allows to ex-
tend the UDT to the multistatic case (transmitter and receiver
are not co-located) where the non-diagonal element of the
scattering matrix can be employed for the image reconstruction
which significantly increases the resolution as a consequence.
B. MUDT Inverse Scattering
From (2) the object function can be determined. Substituting
(3) in (2) with the prime integrand for the second Green’s term,
changing variables to k00
y=ky+k0
yand using 2-D spatial
Fourier definition for the received signal an inner integral
is obtained. The stationary phase method can be applied to
evaluate that inner integral asymptotically for k0zas follows:
(4)
I(k00
y)≈ |˜
Tn(k00
y
2, kz)|2rπ
|An(ky, z, ω)|
ej[k00
znz6˜
Tn(k00
y,k00
zn,tl)+ k00
y
2(ytyr)π
4]
where k00
zn =q4k2
nk00
yand
(5)An(k00
y, z, ω) = k2
n
k3
zn
z+2
∂k2
y
[6˜
Tn]|k00
y
2
Where 6denotes the phase and tlis the thickness of the layer
l(l= 1,2). The term k00
y
2(ytyr)in the phase of the inner
integral is the difference between UDT and MUDT which is
the consequence of considering the problem multistatic rather
than monostatic. In other words, if, in (4) the transmitter and
receiver are located at the same place (monostatic measure-
ment or yt=yr), the UDT formulation will be obtained [4].
However, the non-diagonal elements of the scattering matrix
cannot be used in the inversion scheme and this is the source of
the shadowing image and low resolution in the UDT compare
to the MUDT.
After a straightforward simplification and using the Fourier
transform definition, the object function for the MUDT can
be obtained as follows
(6)
Where ˜
Esct(k00
y, ω)is the spatial Fourier transform of the
received scattered filed, and
˜
Esct(k00
y, ω) = Z+
−∞
Esct(yt, ω)ejk00
yytdyt.(7)
III. MUDT SIMULATION RESULTS
The MUDT method is used to obtain the location of the
unknown scatterers inside the polymer foam and it is used to
compare the results with the UDT. The numerical scattered
field is generated by the use of the time domain solver of
the commercial Software CST Studio Suiterfor a single
layer of the foam and 7x-band open-waveguide antennas
for multistatic transmitting/receiving the signal as shown in
Fig. 3. The distance between two adjacent antennae is 5cm.
Following [9], an antenna de-embedding is performed to relate
the scattering parameters (S-parameters) to the electric field
for MUDT imaging. It is worth mentioning the permittivity
correlates with a certain amount of the moisture (Mn)based
on the wet basis, which is the percentage equivalent of the ratio
of the weight of the water to the weight of the wet foam. Here,
it is assumed that the permittivity of the scatterer is r= 2
which is equivalent to Mn40%. Moreover, additional to
the diagonal elements of the scattering matrix (DT and UDT),
the Si(i+1) (i= 1,2,...,6) is also used in the MUDT for
image reconstruction. Fig. 4(a) shows the reconstructed image
with UDT and Fig, 4(b) shows the reconstructed image with
MUDT. As can be seen from these two figures, with the
MUDT method, a good resolution is obtained. Furthermore,
the shadowing images with MUDT is significantly reduced
compared to the UDT method.
IV. CONCLUSION
A multistatic uniform diffraction tomography is proposed
to obtain the moisture distribution inside a polymer foam in a
Fig. 3. 2-D simulated imaging scenario.
0.0 0.1 0.2 0.3 0.4 0.5
z(m)
0.15
0.10
0.05
0.00
0.05
0.10
0.15
y(m)
0.0
0.2
0.4
0.6
0.8
1.0
0.0 0.1 0.2 0.3 0.4 0.5
z(m)
0.15
0.10
0.05
0.00
0.05
0.10
0.15
y(m)
0.0
0.2
0.4
0.6
0.8
1.0
Fig. 4. Corresponding normalized (Top) UDT (Bottom) MUDT imaging
results.
running belt system in a real-time fashion. MUDT overcomes
low resolution caused by UDT, due to the monostatic nature
of this method, by using the non-diagonal element of the
scattering matrix rather than only the diagonal elements. The
result shows a significant increase in the quality of the final
image. In the next study, we obtain the moisture level inside
the foam after reconstruction of the location of that by defining
an error function and a certain calibration.
ACKNOWLEDGMENT
This project has received funding from the European
Union’s Horizon 2020 research and innovation program under
the Marie Sklodowska-Curie grant agreement No. 764902.
REFERENCES
[1] Y. Sun, “Adaptive and Intelligent Temperature Control of Microwave
Heating Systems with Multiple Sources,” PhD desertion, Karlsruhe
Institute of Technology, 2014.
[2] L. Feher, G. Link, “Hochmodiger Mikrowellenresonator f¨
ur die
hochtemperaturbehandlung von Werkstoffen,”DE19633245C1. Aug. 17,
1996.
[3] G. Link, et al, “Faserverbund-Leichtbau mit Automatisierter
Mikrowellenprozesstechnik hoher Energieeffizienz (FLAME):
Schlussbericht des BMBF-Verbundprojektes (KIT Scien-
tific Reports;7701),” IHM Projects Information, Internet
https://publikationen.bibliothek.kit.edu/1000047509.
[4] K. Ren and R. J. Burkholder, “A Uniform Diffraction Tomographic
Imaging Algorithm for Near-Field Microwave Scanning Through Strat-
ified Media,” IEEE Trans. Antennas Propag., vol. 64, no. 12, pp.
5198–5207, Dec. 2016.
[5] C. T. Tai, “Dyadic Green Functions in Electromagnetic Theory,” 2nd ed.
NY, United Sates, 1994.
[6] W. C. Chew, “Waves and Fields in Inhomogeneous Media,” New York,
NY, USA: IEEE Press, 1995.
[7] A. Omrani, M. Moghadasi, M. Dehmollaian, Localisation and permittiv-
ity extraction of an embedded cylinder using decomposition of the time
reversal operator,” IET Microwaves, Antennas and Propag., vol. 14, no.
9, pp.851-859, July 2020.
[8] D. Dudley, “Mathematical foundations for electromagnetic theory.” New
York: IEEE press, 1994.
[9] S. Sadeghi, K. Mohammadpour-Aghdam, K. Ren, R. Faraji-Dana, and
R. J. Burkholder, “A pole-extraction algorithm for wall characterization
in through-the-wall imaging systems,” IEEE Trans. Antennas Propag.,
vol. 67, no. 11, pp. 7106–7113, Nov. 2019.
... IPT underpins and facilitates the extraction of qualitative and quantitative data regarding the related industrial processes, which is usually visualized in various ways for people to understand its nature, measure the critical process characteristics, and implement process control in a complete feedback network [7]. Some typical representatives of IPT, such as microwave tomography (MWT) [8][9][10][11][12][13][14][15], electrical resistance tomography (ERT) [16], and electrical capacitance tomography (ECT) [17] are widely used for industrial purposes such as moisture detection [8,9], crack detection and powder flow in pipes, and flow pattern detection of granules. In our study, we concentrate on a unique industrial microwave drying process [10] which uses precise drying and heating equipment for polymer foams with the aid of MWT, as displayed in Figure 1. ...
... IPT underpins and facilitates the extraction of qualitative and quantitative data regarding the related industrial processes, which is usually visualized in various ways for people to understand its nature, measure the critical process characteristics, and implement process control in a complete feedback network [7]. Some typical representatives of IPT, such as microwave tomography (MWT) [8][9][10][11][12][13][14][15], electrical resistance tomography (ERT) [16], and electrical capacitance tomography (ECT) [17] are widely used for industrial purposes such as moisture detection [8,9], crack detection and powder flow in pipes, and flow pattern detection of granules. In our study, we concentrate on a unique industrial microwave drying process [10] which uses precise drying and heating equipment for polymer foams with the aid of MWT, as displayed in Figure 1. ...
... Its principal areas of applications are in material processing, for example, thermal curing of fiber composites and drying of porous foams. An MWT system [8] is designed and integrated with the HEPHAISTOS to recover the volumetric information of the moisture location and its level during the drying process of the polymer foam. The power level and pulse duration of the magnetrons will be adjusted based on the input information from the MWT. ...
Article
Full-text available
Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms.
... To apply the TRI, an exact or approximate dyadic Green's function (DGF) of the medium is required [33]. In [34][35][36][37][38][39], only the transmission part of Green's function was considered to locate the target in the multilayered media. However, it is not sufficient to take into account the presence of metal plates or reflecting surfaces below the foam. ...
... The closed-form representation of the DGF is obtained by applying stationary phase approximation (SPA). Here, we would like to emphasise that in diffraction tomography based algorithms, e.g., UDT [38], MUDT [39], incorporating the reflected part will render the integral undefined as the closed form of the object function cannot be evaluated by applying SPA. Furthermore, a new single-frequency (SF) TRI-DORT is introduced based on the behavior of eigenvalues of the time-reversal operator (TRO) to foster high-speed data acquisition. ...
Article
Full-text available
Microwave tomography (MWT) based control is a novel idea in industrial heating systems for drying polymer foam. In this work, an X-band MWT module is designed and developed using a fixed antenna array configuration and integrated with the HEPHAISTOS industrial heating system. A decomposition of the time-reversal operator (DORT) algorithm with a proper Green’s function of multilayered media is utilized to localize the moisture location. The derived Green’s function can be applied to the media with low or high contrast layers. It is shown that the time-reversal imaging (TRI) with the proposed Green’s function can be applied to the multilayered media with a moderately rough surface. Moreover, a single frequency TRI is proposed to decrease the measurement time. Numerical results for different moisture scenarios are presented to demonstrate the efficacy of the proposed method. The developed method is then tested on the experimental data for different moisture scenarios from our developed MWT experimental prototype. Image reconstruction results show promising capabilities of the TRI algorithm in estimating the moisture location in the polymer foam.
... In this work, a multistatic uniform diffraction tomography algorithm (MUDT) for multilayered media is proposed [15]. The MUDT algorithm developed here specially caters for the measurement case of a multiple-input multiple-output fixed array sensor configuration. ...
Article
Microwave tomography (MWT) based control is a novel idea in industrial heating systems that demands fast DAQ and real-time imaging algorithms. Uniform diffraction tomography (UDT) is one such technique that can provide real-time imaging. However, its single-input single-output data based inverse scattering formulation can lead to time-consuming DAQ. In this article, a multistatic uniform diffraction tomography (MUDT) imaging algorithm is proposed for a fixed array MWT system. The MWT system is integrated into the industrial heating unit HEPHAISTOS to estimate the moisture distribution in a polymer foam. In addition, a technique is presented to retrieve the electrical properties of the targets using reconstructed information from MUDT and by investigating the singular values of multistatic scattering data. Through numerical and experimental data for the considered moisture scenarios, the MUDT approach is tested, and its comparison with the UDT approach is shown. Reconstructed results show that in comparison to UDT, the MUDT approach i) eliminates the need for mechanical scanning, ii) provides aliasing-free images by following Nyquist sampling criteria, and iii) can resolve multiple targets in the imaging media with significant improvement in the spatial resolution that further augments in the correct retrieval of the dielectric constants of the target.
... The MWT senor setup consists of open-ended waveguide antennas operating in Xband range. The selection of the frequency and the antenna type for the MWT sensor array are detailed in [11]. For estimating the moisture levels (in terms of dielectric constant) in a porous material with a large cross-sectional dimension, we apply a statistical inversion approach [12] based on the Bayesian framework. ...
Article
Full-text available
When using the statistical inversion framework in microwave tomography (MWT), generally, the real and imaginary parts of the unknown dielectric constant are treated as uncorrelated and independent random variables. Thereby, in the maximum a posteriori estimates, the two recovered variables may show different structural changes inside the imaging domain. In this work, a correlated sample-based prior model is presented to incorporate the correlation of the real part with the imaginary part of the dielectric constant in the statistical inversion framework. The method is used to estimate the inhomogeneous moisture distribution (as dielectric constant) in a large cross section of polymer foam. The targeted application of MWT is in industrial drying to derive intelligent control methods based on tomographic inputs for selective heating purposes. One of the features of the proposed method shows how to integrate lab-based dielectric characterization, often available in MWT application cases, in the prior modeling. The method is validated with numerical and experimental MWT data for the considered moisture distributions.
... That is not sufficient to provide efficient control of microwave sources. Thus, integration of microwave tomography (MWT) imaging modality operating in X-band range [7] (from 8 GHz to 12 GHz) with the drying system is proposed (see number Tag 4 in Figure 1) to estimate the moisture content distribution in a polymer foam. Based on the MWT tomographic output, an intelligent control strategy for power sources can be derived. ...
Article
Full-text available
The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities.
... Thus, results in better resolution than UDT. Also, under condition 1) the low number of antennas, and 2) if two adjacent antennas are not in close vicinity to each other, the UDT imaging algorithm fails to truly reconstruct the location of the scatterer [5]. With this combined approach, more accurate estimates can be obtained with improved computational time. ...
Conference Paper
Full-text available
In this work, a multistatic uniform diffraction tomography (MUDT) method, that was proposed by the authors as a new qualitative imaging method just recently, is combined with the quantitative Bayesian inversion framework. In this combined approach, MUDT is applied to find the location of the moisture and this localization is employed as a pre-knowledge for the Bayesian framework to estimate the moisture levels in a polymer foam. The proposed combined algorithm might become a major part of the development of a new kind of intelligent industrial microwave drying systems. The imaging algorithm is tested with simulated measurement data. The frequency band from 8 GHz to 12 GHz (X-band) is used for the MUDT algorithm whereas a single frequency of 8.2 GHz is assumed for the Bayesian framework. The first results demonstrate the ability of the developed combined algorithm for optimizing the computational load unlike seen in the quantitative inversion approaches.
Article
In this work, a quantitative Bayesian inversion framework for microwave tomography (MWT) is coupled with a multistatic uniform diffraction tomography (MUDT) method to improve the imaging quality. The method is applied for an industrial use-case of MWT in which we estimate the 2-D spatial distribution of moisture (in terms of dielectric constant) in a polymer foam. In essence, we modify the prior information in the single-frequency Bayesian inversion framework using high-resolution complementary structural information of the imaging domain from a qualitative approach MUDT utilizing broadband frequency-domain data. This way of obtaining structural prior information is effective as it utilizes the data from the same microwave sensor setup in contrast to the frequency-hopping approach, priors derived for other imaging modalities or radar-based techniques with the co-located sensor using, for example, uniform diffraction tomography (UDT) inversion framework. Proposed algorithm performance is tested for different moisture scenarios in the polymer foam with 3D numerical and experimental data from our developed MWT system. It is shown that the proposed approach significantly improves the reconstruction accuracy for the considered cases over just using the Bayesian inversion approach.
Conference Paper
Full-text available
To reduce carbon dioxide (CO2) emissions while keeping up with the increasing demand of energy, new energy sources and new energy storage systems must be developed; hydrogen is expected to play an essential role in the transition to lesser CO2-footprint energy. Traditionally hydrogen (H2) production is based on natural gas steam reforming, which results in the associated CO2 emissions. Alternative sources of H2 production are water electrolysis and direct methane decomposition, the latter having a much smaller theoretical energy cost per unit of produced H2. This paper concerns the characterization of H2 production via methane plasmalysis in the South Beach Module prototype, a 2.45 GHz microwave reactor working at atmospheric pressure. The experimental protocol takes into consideration various gas mixture constituents and operating conditions (e.g., gas flow rate, microwave input power, as to optimize the decomposition of methane molecule into hydrogen gas and solid carbon. The economics of microwave-assisted plasma methane decomposition as a hydrogen source are taken into consideration.
Conference Paper
Full-text available
Augmented Reality (AR), as a variation of Virtual Reality (VR), has been proved useful for decades. However, it is not widely utilized in most industries. To fill the gap between this technique and industrial usage, we propose a novel AR system in the context of industrial process tomography (IPT). As the pioneering AR deployment in IPT, this system offers a new solution to underpin the onsite data analysis regarding volumetric visualization. In our work, an endeavor to provide intelligent control for an industrial drying system is pursued by using microwave tomography (MWT), a breed of IPT, as an imaging modality. Here, the AR system is integrated with the MWT for post processing of its volumetric images, containing critical information of the industrial process. The core part of the AR system is implemented by an interactive mobile app that is supported on iOS/Android platforms. The overall system is generalized by four distinctive findings: interactivity, mobility, information richness, and mutual collaboration. Our proposed system opens the horizon of leveraging AR in IPT to benefit domain-related users regarding onsite data analysis and visualization.
Article
Full-text available
In this study, first, the problem of time reversal imaging of an embedded dielectric or metallic cylinder inside another dielectric cylinder is studied. The direct problem is carried out numerically using the finite-element method. The background dyadic Green function (DGF) is computed analytically by computing radiated fields of an infinitesimal electric dipole near an infinitely long dielectric cylinder. The time reversal technique is then applied using this background DGF to image the embedded cylinder. Results demonstrate that while using a free-space DGF for imaging yields erroneous results, by employing a proper background DGF, the scatterer inside the cylinder is correctly localised. Next, the authors extract permittivities in two different scenarios with two different techniques. In the first case, the permittivity of a background cylinder that contains a metallic cylinder inside it is extracted by calculating the image entropy. In the second case, the permittivity of an embedded cylinder inside a priori known background dielectric cylinder is estimated by a new method based on an optimisation and evaluation of the largest eigenvalues of the multistatic data matrices. The proposed techniques are then verified using simulated and measured data. For measurements, a newly developed combined tapered sectorial antenna is designed, fabricated, and characterised.
Article
Full-text available
Estimation of wall parameters is critical for focused through-the-wall imaging (TWI). In this paper, a novel algorithm based on pole extraction and wall reflection coefficients is presented to accurately estimate the essential parameters of a multi-layered wall. The generalized pencil of function (GPOF) is applied to decompose the frequency domain received signal into a summation of ordered exponential terms and phase delays. Matching the terms with the multiple wall reflections provides equations for extracting the parameters. A frequency domain calibration process is proposed to remove the antenna response from the measured wall response. The formulation of the proposed parameter extraction and calibration algorithms is presented along with simulated and measured results for validation. The efficacy of the method is demonstrated on a real through-the-wall imaging system.
Article
A 2D near-field uniform diffraction tomographic (UDT) imaging algorithm is formulated to generate images of targets embedded in a layered structure. The conventional diffraction tomography (DT) improperly applies the stationary phase method for stratified environments to reduce the innermost spectral integral. In DT the large argument is assumed to be the depth, which is not appropriate for near-field imaging. This results in amplitude discontinuities occurring at the interfaces between adjacent layers. The correct large argument is the free space wavenumber as used in high-frequency asymptotic solutions. The UDT therefore yields uniformly continuous images across the interfaces. And like the DT, the UDT retains the fast Fourier transform (FFT) relation in the algorithm for generating images very efficiently. Numerical and experimental image comparisons between DT and UDT for objects buried in stratified environments are presented to demonstrate the efficacy of the proposed UDT method.
Article
Co-published with Oxford University Press. This highly technical and thought-provoking book stresses the development of mathematical foundations for the application of the electromagnetic model to problems of research and technology. Features include in-depth coverage of linear spaces, Green’s functions, spectral expansions, electromagnetic source representations, and electromagnetic boundary value problems. This book will be of interest graduate-level students in engineering, electromagnetics, physics, and applied mathematics as well as to research engineers, physicists, and scientists. © 1994 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Hochmodiger Mikrowellenresonator für die hochtemperaturbehandlung von Werkstoffen
  • L Feher
  • G Link
L. Feher, G. Link, "Hochmodiger Mikrowellenresonator für die hochtemperaturbehandlung von Werkstoffen,"DE19633245C1. Aug. 17, 1996.
Waves and Fields in Inhomogeneous Media
  • W C Chew
W. C. Chew, "Waves and Fields in Inhomogeneous Media," New York, NY, USA: IEEE Press, 1995.
Faserverbund-Leichtbau mit Automatisierter Mikrowellenprozesstechnik hoher Energieeffizienz (FLAME): Schlussbericht des BMBF-Verbundprojektes (KIT Scientific Reports;7701)
  • G Link
Hochmodiger Mikrowellenresonator f&#x00FC;r die hochtemperaturbehandlung von Werkstoffen
  • feher