scholarly journals Extraction of Weak Scatterer Features Based on Multipath Exploitation in Radar Imagery

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Muhannad Almutiry ◽  
Lorenzo Lo Monte ◽  
Michael C. Wicks

We proposed an improved solution to two problems. The first problem is caused by the sidelobe of the dominant scatterer masking a weak scatterer. The proposed solution is to suppress the dominant scatterer by modeling its electromagnetic effects as a secondary source or “extra dependent transmitter” in the measurement domain. The suppression of the domain scatterer reveals the presence of the weak scatterer based on exploitation of multipath effects. The second problem is linearizing the mathematical forward model in the measurement domain. Improving the quantity of the prediction, including multipath scattering effects (neglected under the Born approximation), allows us to solve the inverse problem. The multiple bounce (multipath) scattering effect is the interaction of more than one target in the scene. Modeling reflections from one target towards another as a transmitting dipole will add the multiple scattering effects to the scattering field and permit us to solve a linear inverse problem without sophisticated solutions of a nonlinear matrix in the forward model. Simulation results are presented to validate the concept.

2020 ◽  
Vol 238 ◽  
pp. 06019
Author(s):  
Thomas van der Sijs ◽  
Omar El Gawhary ◽  
Paul Urbach

Electromagnetic scattering is the main phenomenon behind all optical measurement methods where one aims to retrieve the shape or physical properties of an unknown object by measuring how it scatters an incident optical field. Such an inverse problem is often approached by solving, several times, the corresponding direct scattering problem and trying to find the best estimate of the object which is compatible with a set of measurements. In the direct scattering problem, two regimes can be distinguished depending on the size of the object and the permittivity contrast: the weak-scattering regime and the strong-scattering regime. Generally, the presence of the scatterer alters the form of the incident field inside the scatterer. If that effect is neglected in the physical model, then one speaks of the so-called single-scattering regime or, more often, the Born approximation. The regime in which this approximation is valid is the weak-scattering regime. The corresponding inverse problem, that aims to retrieve the object from scattering data, becomes linear in this case. Linearizing the problem simplifies the method to solve it, but also introduces limitations to the maximum spatial resolution achievable in the reconstruction of the object. In the strong-scattering regime, multiple-scattering effects are not neglected and the inverse problem is treated in its full non-linear nature, which makes finding its solution a far more challenging task. Despite the existence of numerical methods, a powerful way to solve those direct problems would be to use a perturbation approach where the field is expressed as a series, known as the Born series. The advantage of a perturbation approach stems from the fact that each term of the series has a clear physical meaning and can unveil much more about the scattering process than a purely numerical approach can offer. Unfortunately, the series solution turns out to be strongly divergent in the strong-scattering regime, making it an unpractical approach for problems under these strong-scattering conditions. Thus, despite the fact that multiple scattering could, in principle, allow resolving sub-wavelength details of the unknown object, this possibility is in practice hampered by the divergent nature of the higher-order terms of the Born series. In this work, we show how to solve this problem by employing Padé approximants and how to treat electromagnetic problems well beyond the weak-scattering regime and provide an accurate evaluation of the scattered field even under strong-scattering conditions. Padé approximants are rational functions that can offer improvements in two ways, namely series acceleration of converging series and analytic continuation of a series outside its region of convergence. In the case of a symmetric approximant of order N, the approximant is calculated from 2N + 1 terms in the Born series, therefore incorporating multiple-scattering effects to which these higher-order corrections in the Born series correspond. We apply the method to two scalar scattering problems: that of a one-dimensional slab and that of an infinitely long cylinder, which reduces to a two-dimensional problem under normal incidence. In particular, we treat cases in the strong-scattering regime where the Born series diverges, but where Padé approximation retrieves a valuable result. In Fig. 1 the case of a cylinder is shown which is well beyond the weak-scattering regime, but where the most accurate Padé approximant gives a good result for the field. The presented approach incorporates multiple-scattering effects and can therefore represent an important building block to the application of the Born series to direct and inverse problems, with potential applications in superresolution, optical metrology, and phase retrieval.


2020 ◽  
Vol 17 (4) ◽  
pp. 616-620 ◽  
Author(s):  
Songlin Lei ◽  
Xiaolan Qiu ◽  
Yueting Zhang ◽  
Lijia Huang ◽  
Ding Chibiao

2021 ◽  
Vol 2128 (1) ◽  
pp. 012016
Author(s):  
Nihal A. Mabrouk ◽  
Abdelreheem M. Khalifa ◽  
Abdelmenem A. Nasser ◽  
Moustafa H. Aly

Abstract Our paper introduces a new technique for diagnosis of various heart diseases without the need of highly experts to investigate the electrocardiogram (ECG). Using the same electrodes of the ECG machine, it will be able to transmit directly the electrical activity inside the heart to a moving picture. Our technique is based on artificial intelligence algorithm using artificial neural networks (ANN). Finding the trans-membrane potential (TMP) inside the heart from the body surface potential (BSP) is known as the inverse problem of ECG. To have a unique solution for the inverse problem the data used should be obtained from a forward model. A three dimensional (3-D) model of cellular activation whole heart embedded in torso is simulated and solved using COMSOL Multiphysics software. In our previous paper, one ANN succeeded in displaying the wave propagation on the surface of a normal heart. In this paper, we used a configuration of ANNs to display different cases of heart with myocardial infarction (MI). To check the system accuracy, eight MI cases with different sizes and locations in the heart are simulated in the forward model. This configuration proved to be highly accurate in displaying each MI case -size and location- presenting the infarction as an area with no electrical activity.


2021 ◽  
Author(s):  
Huseyin Ozgur Kazanci

Abstract Diffuse Optical Tomography (DOT) imaging technique has been interesting research field for researchers since it has uncertainties in the solution space. DOT modality is unsolved scientific problem. Inverse problem solution and image reconstruction has never been in its best quality. Reconstructed images have low spatial resolution. Scattering nature of diffusive light is the obscuring effect for DOT modality. DOT has 3 functional sub-branches which of these are Continuous Wave (CW), Time-Resolved (TR), and Frequency-Domain (FD). In this work, one new approach to Frequency Domain Diffuse Optical Tomography (FDDOT) biomedical optic imaging modality is presented to the readers. Frequency Shifting data were added to the forward model problem which basically has source-detector couplings and number of imaging voxels. 100 MHz center core light modulation frequency was selected. 169 source-detector matches were used on back-reflected imaging geometry. Absorption coefficient ma was selected 0.1 cm− 1. Scattering coefficient µs was selected 100 cm− 1. 1 micrometer x, y, z cartesian grid coordinates were used in each direction for imaging tissue-like simulation media. The total of 100 frequency shift was added to the forward model problem which has 5 Hz frequency step. 2 inclusion objects were embedded inside the imaging simulation phantom. 2 inclusion images were successfully reconstructed with the low contrast to noise ratio (CNR) error and position error (PE). Frequency shifting technique is first applied for FDDOT here. This technique has increased the total number of equations in the forward model problem; hence it is helping to solve the inverse problem. In this work, the positive effect of using multi frequency methodology was observed. Differentiation of 2 embedded inclusions was successfully completed and illustrated in this work.


2007 ◽  
Vol 353-358 ◽  
pp. 2371-2374 ◽  
Author(s):  
Ji Seong Hwang ◽  
Jong Woo Jun ◽  
Se Ho Choi ◽  
Cheol Woong Kim ◽  
Kazuhiro Ogawa ◽  
...  

Nondestructive testing using magnetic field is useful for detection of a crack on ferromagnetic material. The magnetic field distribution has to be obtained for quantitative evaluation of crack direction, size, and shape. Also, a crack can be evaluated by using the inverse problem analysis. However, an analysis method using a dipole model can be used to analyze the magnetic field distribution around a crack at a higher speed than the finite element method (FEM). Therefore, a dipole model simulation can provide useful information which can be used for the inverse problem analysis. However, the magnetic charge per unit area, m, and the permeability, μ, has been treated as constants. Therefore, analyzed results have been different from experimental results in most cases. This paper proposes the improved dipole model simulation method, which assumes that the magnetic charges per unit area exist at the section areas, edge lines and summits of a crack. Also, the magnetic charges per unit area were assumed to depend on the square of the crack depth. The improved method is validated by comparing its results with the experiment results obtained with the use of the magnetic camera.


2008 ◽  
Vol 65 (9) ◽  
pp. 2803-2823 ◽  
Author(s):  
T. Vukicevic ◽  
D. Posselt

Abstract In this study, the relationship between nonlinear model properties and inverse problem solutions is analyzed using a numerical technique based on the inverse problem theory formulated by Mosegaard and Tarantola. According to this theory, the inverse problem and solution are defined via convolution and conjunction of probability density functions (PDFs) that represent stochastic information obtained from the model, observations, and prior knowledge in a joint multidimensional space. This theory provides an explicit analysis of the nonlinear model function, together with information about uncertainties in the model, observations, and prior knowledge through construction of the joint probability density, from which marginal solution functions can then be evaluated. The numerical analysis technique derived from the theory computes the component PDFs in discretized form via a combination of function mapping on a discrete grid in the model and observation phase space and Monte Carlo sampling from known parametric distributions. The efficacy of the numerical analysis technique is demonstrated through its application to two well-known simplified models of atmospheric physics: damped oscillations and Lorenz’s three-component model of dry cellular convection. The major findings of this study include the following: (i) Use of a nonmonotonic forward model in the inverse problem gives rise to the potential for a multimodal posterior PDF, the realization of which depends on the information content of the observations and on observation and model uncertainties. (ii) The cumulative effect of observations over time, space, or both could render the final posterior PDF unimodal, even with the nonmonotonic forward model. (iii) A greater number of independent observations are needed to constrain the solution in the case of a nonmonotonic nonlinear model than for a monotonic nonlinear or linear forward model for a given number of degrees of freedom in control parameter space. (iv) A nonlinear monotonic forward model gives rise to a skewed unimodal posterior PDF, implying a well-posed maximum likelihood inverse problem. (v) The presence of model error greatly increases the possibility of capturing multiple modes in the posterior PDF with the nonmonotonic nonlinear model. (vi) In the case of a nonlinear forward model, use of a Gaussian approximation for the prior update has a similar effect to an increase in model error, which indicates there is the potential to produce a biased mean central estimate even when observations and model are unbiased.


2006 ◽  
Vol 2006 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaolei Song ◽  
Ji Yi ◽  
Jing Bai

Based on an independent forward model in fluorescent tomography, a parallel reconstructed scheme for inhomogeneous mediums with unknown absorption property is proposed in this paper. The method considers the two diffusion equations as separately describing the propagation of excited light in tissues with and without fluorescent probes inside. Then the concentration of fluorophores is obtained directly through the difference between two estimations of absorption coefficient which can be parallel inversed. In this way, the multiparameter estimation problem in fluorescent tomography is transformed into two independent single-coefficient determined schemes of diffusion optical tomography (DOT). Any algorithms proved to be efficient and effective in DOT can be directly applied here. In this study the absorption property is estimated from the independent diffusion equations by a gradient-based optimization method with finite element method (FEM) solving the forward model. Simulation results of three representative occasions show that the reconstructed method can well estimate fluorescent property and tissue absorption distribution.


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