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This study introduces a new broadband hybrid perfect absorber (HA) that includes metamaterial absorber (MA) and a lossy composite. The unit cell of the MA is in the form of two concentric ring-based structures fabricated on an FR4 substrate, which provides a broadband absorption band because of two neighbouring resonance frequencies. The composite layer is built by mixing the carbon black powder and epoxy resin in an optimised weight percentage. By modelling the structure with multiple transmission line sections, a closed-form procedure has been proposed to optimise the HA parameters. The final tuning of the HA parameters is performed using HFSS. A prototype of the HA is fabricated and measured. The results indicate that the proposed HA provides nearly perfect absorption (absorption ratio over 99%) in the frequency range of 2–2.8 GHz. It is, also, polarisation-insensitive due to its symmetrical design. The total thickness of the proposed structure is 12.5 mm, which is acceptable concerning the absorption rate and the operational frequency bandwidth. [ABSTRACT FROM AUTHOR]

Some methods developed in reversible data hiding (RDH) make use of prediction for data embedding for original pixel estimation. Predicators may also be exploited in RDH in encrypted image (RDHEI); this has become a research interest in recent years because of the development of cloud computing and a need for content owner privacy. This paper presents a high-capacity reversible data hiding in encrypted image (RDHEI) that employs local difference predictor. In this algorithm, an image is divided into non-overlapping blocks. In each block, the central pixel of the block is considered as the leader pixel and others as follower ones. The prediction errors between the intensity of the follower pixels and leader one are calculated using local difference predictor and analyzed to determine a label for block embedding capacity. This label indicates the amount of data that can be embedded in a block after encryption. Using this pre-processing for all blocks, we vacate rooms before the encryption of the original image to achieve high embedding capacity. Also, using these labels, embedded data is extracted and the original image is losslessly reconstructed at the decoding phase. Comparing to existent RDHEI algorithms, not only embedding capacity is increased by the proposed algorithm, but also a perfect reconstruction of the original image is realized by content owner without having data hider key. Experimental results confirm that the proposed algorithm outperforms state of the art RDHEI methods. [ABSTRACT FROM AUTHOR]

This paper presents a linear synthetic focusing method (SFM) in order to mitigate the drawbacks of the classical multiple signal classification (MUSIC) algorithm for microwave imaging (MI). The determination of noise subspace dimension for MUSIC algorithm is a challenge when imaging an extended target. That is because an extended target comprises many point scatterers and a practical MI system provides an incomplete multistatic response (IMSR) matrix. The SFM obtains a focused multistatic response matrix for each location in the imaging region, which contains, mostly, the scattered field of a point scatterer at that location. In this way, the signal subspace is reduced to the one for a point scatterer, whose singular values are well-separated from those of the noise subspace. The proposed SFM is applied to the breast cancer detection using synthetic data. It is also applied to the experimental data given by Institute Fresnel to test the SFM for scenarios other than biomedical uses. It is shown that the SFM provides superior results over the classical MUSIC algorithm, especially for extended targets and IMSR matrices. [ABSTRACT FROM AUTHOR]

A calibration technique for free-space measurement of the permittivity and conductivity has been developed, taking account of antenna-medium coupling. Thus, the accuracy is improved compared to previously used calibration. Two examples are given to illustrate this improvement.

An inverse scattering method for the reconstruction of the permittivity and conductivity profiles of a multilayered medium and for that of the impedance profile of a nonuniform transmission line is proposed. The inversion is based on the global minimization of an objective function by the multilevel single-linkage method. The objective function is defined as the mean-square error between the measured data and the data obtained from the solution of the forward problem. An exact formulation for the gradient of the objective function in closed form is derived. The necessary condition for the unique solution of the inverse problem of a nonuniform transmission line is discussed. Reconstruction examples using both experimental and noisy synthetic data are presented. Index Terms--Inverse scattering, nonhomogeneous media.

This letter focuses on the modification of a unit cell of a metamaterial absorber to decrease its operational frequency. By decreasing the operational frequency, we can increase capability of the absorber for practical applications and decrease sensitivity of the structure response to the curvature. The structure has been implemented by the array of the unit cell on the FR4 substrate in the front of a conductive plate. Both the simulated and experimental results indicate the structure provides 20% decrease in the minimum operation frequency with respect to the reference structure. Also, the operating frequency range of the structure with absorptivity more than 90% is 1.35–3.5 GHz, i.e., 88% fractional bandwidth. The structure has appropriate response under oblique incident angle from 0° to 40°. [ABSTRACT FROM AUTHOR]

Multiple signal classification (MUSIC) method uses the multi-static response matrix (MSR) to locate small inclusions in a microwave imaging (MI) system. The MSR cannot accommodate all available data in an actual MI system because practical restrictions make some receivers be inactive for every active transmitter. The current work presents a method for completing the MSR acquired in practical systems. Using the least squares method, the complete MSR matrix is formed by the estimation of its unknown elements, associated to the signal at inactive receivers. The estimation algorithm employs the signal of other active receivers to obtain inactive receiver signals. In this way, all available data contributes in imaging, which improves the localization performance. The merits of our proposal are demonstrated using the Institut Fresnel experimental data sets as well as various realistic synthetic data. [ABSTRACT FROM PUBLISHER]

Multiple signal classification (MUSIC) is a high-resolution method in microwave imaging which is severely based on the number of singular values of a multistatic response matrix. However, the role of noise and multiple scattering is crucial to determine the true dimension of the signal subspace. In this article, we show that in the presence of multiple scattering between the targets, some singular values of the signal subspace will greatly be decreased which is a critical point when the noise is added to the system. In this case, these signal singular values will mix with the noise ones and the most popular MUSIC methods degrade and even fail to estimate closely spaced target locations. Here, we introduce a method to solve the ambiguity in determining the number of targets employing a pre-processing method, discrete stationary wavelet transform (DSWT). The DSWT is developed on the basis of features of the reflection coefficient between targets. The application of this algorithm to measurement data shows its superiority over another thresholding-based algorithm, empirical mode decomposition. The results indicate that DSWT+MUSIC yields accurate estimate of the target locations, even in the presence of considerable noise and multiple scattering in the received signal. [ABSTRACT FROM PUBLISHER]

This paper presents an analytical method to estimate the location and number of actual small targets in 2Dinverse scattering problems. This method is motivated from the exact maximum likelihood estimation of signal parameters in white Gaussian noise for the linear data model. In the first stage, the method uses the MUSIC algorithm to acquire all possible target locations and in the next stage, it employs an analytical formula thatworks as a spatial filter to determine which target locations are associated to the actual ones. The ability of the method is examined for both the Born and multiple scattering cases and for the cases of well-resolved and non-resolved targets. Many numerical simulations using both the coincident and non-coincident arrays demonstrate that the proposed method can detect the number of actual targets even in the case of very noisy data and when the targets are closely located. Using the experimental microwave data sets, we further show that this method is successful in specifying the number of small inclusions. [ABSTRACT FROM AUTHOR]

This article introduces a recursive formula, in which any approximate method can, iteratively, be incorporated to solve electromagnetic scattering problems. The use of extended Born approximation and quasi-analytical approximation in this formula results in two series (algorithms), whose convergence properties are discussed. Numerical examples are given to demonstrate merits and the range of applicability of the new series. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 2425–2429, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22781 [ABSTRACT FROM AUTHOR]