1,619 research outputs found
Direct sampling method for anomaly imaging from S-parameter
In this paper, we develop a fast imaging technique for small anomalies
located in homogeneous media from S-parameter data measured at dipole antennas.
Based on the representation of S-parameters when an anomaly exists, we design a
direct sampling method (DSM) for imaging an anomaly and establishing a
relationship between the indicator function of DSM and an infinite series of
Bessel functions of integer order. Simulation results using synthetic data at
f=1GHz of angular frequency are illustrated to support the identified structure
of the indicator function.Comment: 6 pages, 6 figure
Real-time microwave imaging of unknown anomalies via scattering matrix
We consider an inverse scattering problem to identify the locations or shapes
of unknown anomalies from scattering parameter data collected by a small number
of dipole antennas. Most of researches does not considered the influence of
dipole antennas but in the experimental simulation, they are significantly
affect to the identification of anomalies. Moreover, opposite to the
theoretical results, it is impossible to handle scattering parameter data when
the locations of the transducer and receiver are the same in real-world
application. Motivated by this, we design an imaging function with and without
diagonal elements of the so-called scattering matrix. This concept is based on
the Born approximation and the physical interpretation of the measurement data
when the locations of the transducer and receiver are the same and different.
We carefully explore the mathematical structures of traditional and proposed
imaging functions by finding relationships with the infinite series of Bessel
functions of integer order. The explored structures reveal certain properties
of imaging functions and show why the proposed method is better than the
traditional approach. We present the experimental results for small and
extended anomalies using synthetic and real data at several angular frequencies
to demonstrate the effectiveness of our technique.Comment: 20 page
Subspace migration for imaging of thin, curve-like electromagnetic inhomogeneities without shape information
It is well-known that subspace migration is stable and effective
non-iterative imaging technique in inverse scattering problem. But, for a
proper application, geometric features of unknown targets must be considered
beforehand. Without this consideration, one cannot retrieve good results via
subspace migration. In this paper, we identify the mathematical structure of
single- and multi-frequency subspace migration without any geometric
consideration of unknown targets and explore its certain properties. This is
based on the fact that elements of so-called Multi-Static Response (MSR) matrix
can be represented as an asymptotic expansion formula. Furthermore, based on
the examined structure, we improve subspace migration and consider the
multi-frequency subspace migration. Various results of numerical simulation
with noisy data support our investigation.Comment: 15 pages, 32 figures. arXiv admin note: text overlap with
arXiv:1404.237
Structure and properties of linear sampling method for perfectly conducting, arc-like cracks
We consider the imaging of arbitrary shaped, arc-like perfectly conducting
cracks located in the two-dimensional homogeneous space via linear sampling
method. Based on the structure of eigenvectors of so-called Multi Static
Response (MSR) matrix, we discover the relationship between imaging functional
adopted in the linear sampling method and Bessel function of integer order of
the first kind. This relationship tells us that why linear sampling method
works for imaging of perfectly conducting cracks in either Transverse Magnetic
(Dirichlet boundary condition) and Transverse Electric (Neumann boundary
condition), and explains its certain properties. Furthermore, we suggest
multi-frequency imaging functional, which improves traditional linear sampling
method. Various numerical experiments are performed for supporting our
explores.Comment: 17 pages, 16 figure
A novel study on subspace migration for imaging of a sound-hard arc
In this study, the influence of a test vector selection used in subspace
migration to reconstruct the shape of a sound-hard arc in a two-dimensional
inverse acoustic problem is considered. In particular, a new mathematical
structure of imaging function is constructed in terms of the Bessel functions
of the order 0, 1, and 2 of the first kind based on the structure of singular
vectors linked to the nonzero singular values of a Multi-Static Response (MSR)
matrix. This structure indicates that imaging performance of subspace migration
is highly related to the unknown shape of arc. The simulation results with
noisy data indicate support for the derived structure.Comment: 9 pages, 12 figure
Multi-frequency topological derivative for approximate shape acquisition of curve-like thin electromagnetic inhomogeneities
In this paper, we investigate a non-iterative imaging algorithm based on the
topological derivative in order to retrieve the shape of penetrable
electromagnetic inclusions when their dielectric permittivity and/or magnetic
permeability differ from those in the embedding (homogeneous) space. The main
objective is the imaging of crack-like thin inclusions, but the algorithm can
be applied to arbitrarily shaped inclusions. For this purpose, we apply
multiple time-harmonic frequencies and normalize the topological derivative
imaging function by its maximum value. In order to verify its validity, we
apply it for the imaging of two-dimensional crack-like thin electromagnetic
inhomogeneities completely hidden in a homogeneous material. Corresponding
numerical simulations with noisy data are performed for showing the efficacy of
the proposed algorithm.Comment: 25 pages, 28 figure
Multi-frequency subspace migration for imaging of perfectly conducting, arc-like cracks
Multi-frequency subspace migration imaging technique are usually adopted for
the non-iterative imaging of unknown electromagnetic targets such as cracks in
the concrete walls or bridges, anti-personnel mines in the ground, etc. in the
inverse scattering problems. It is confirmed that this technique is very fast,
effective, robust, and can be applied not only full- but also limited-view
inverse problems if suitable number of incident and corresponding scattered
field are applied and collected. But in many works, the application of such
technique is somehow heuristic. Under the motivation of such heuristic
application, this contribution analyzes the structure of imaging functional
employed in the subspace migration imaging technique in two-dimensional inverse
scattering when the unknown target is arbitrary shaped, arc-like perfectly
conducting cracks located in the homogeneous two-dimensional space. Opposite to
the Statistical approach based on the Statistical Hypothesis Testing, our
approach is based on the fact that subspace migration imaging functional can be
expressed by a linear combination of Bessel functions of integer order of the
first kind. This is based on the structure of the Multi-Static Response (MSR)
matrix collected in the far-field at nonzero frequency in either Transverse
Magnetic (TM) mode or Transverse Electric (TE) mode. Explored expression of
imaging functionals gives us certain properties of subspace migration and an
answer of why multi-frequency enhances imaging resolution. Particularly, we
carefully analyze the subspace migration and confirm some properties of imaging
when a small number of incident field is applied. Consequently, we simply
introduce a weighted multi-frequency imaging functional and confirm that which
is an improved version of subspace migration in TM mode.Comment: 42 pages, 41 figure
Asymptotic properties of MUSIC-type imaging in two-dimensional inverse scattering from thin electromagnetic inclusions
The main purpose of this paper is to study the structure of the well-known
non-iterative MUltiple SIgnal Classification (MUSIC) algorithm for identifying
the shape of extended electromagnetic inclusions of small thickness located in
a two-dimensional homogeneous space. We construct a relationship between the
MUSIC-type imaging functional for thin inclusions and the Bessel function of
integer order of the first kind. Our construction is based on the structure of
the left singular vectors of the collected multistatic response matrix whose
elements are the measured far-field pattern and the asymptotic expansion
formula in the presence of thin inclusions. Some numerical examples are shown
to support the constructed MUSIC structure.Comment: 19 pages, 7 figure
Analysis of a multi-frequency electromagnetic imaging functional for thin, crack-like electromagnetic inclusions
Recently, a non-iterative multi-frequency subspace migration imaging
algorithm was developed based on an asymptotic expansion formula for thin,
curve-like electromagnetic inclusions and the structure of singular vectors in
the Multi-Static Response (MSR) matrix. The present study examines the
structure of subspace migration imaging functional and proposes an improved
imaging functional weighted by the frequency. We identify the relationship
between the imaging functional and Bessel functions of integer order of the
first kind. Numerical examples for single and multiple inclusions show that the
presented algorithm not only retains the advantages of the traditional imaging
functional but also improves the imaging performance.Comment: 15 pages, 20 figure
Topological derivative-based technique for imaging thin inhomogeneities with few incident directions
Many non-iterative imaging algorithms require a large number of incident
directions. Topological derivative-based imaging techniques can alleviate this
problem, but lacks a theoretical background and a definite means of selecting
the optimal incident directions. In this paper, we rigorously analyze the
mathematical structure of a topological derivative imaging function, confirm
why a small number of incident directions is sufficient, and explore the
optimal configuration of these directions. To this end, we represent the
topological derivative based imaging function as an infinite series of Bessel
functions of integer order of the first kind. Our analysis is supported by the
results of numerical simulations.Comment: 14 pages, 29 figure
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