A simulation-based optimization approach to design of phase excitation tapers for linear phased antenna arrays is presented. The design optimization process is accelerated by means of Surrogate-Based Optimization (SBO); it uses a coarse-mesh surrogate of the array element for adjusting the array’s active reflection coefficient responses and a fast surrogate of the antenna array radiation pattern. The primary optimization objective is to minimize side-lobes in the principal plane of the radiation pattern while scanning the main beam. The optimization outcome is a set of element phase excitation tapers versus the scan angle. The design objectives are evaluated at the high fidelity level of description using simulations of the discrete electromagnetic model of the entire array so that the effects of element coupling and other possible interaction within the array structure are accounted for. At the same time, the optimization process is fast due to SBO. Performance and numerical cost of the approach are demonstrated by optimizing a 16-element linear array of microstrip antennas. Experimental verification has been carried out for a manufactured prototype of the optimized array. It demonstrates good agreement between the radiation patterns obtained from simulations and from physical measurements (the latter constructed through superposition of the measured element patterns).

Most receiving antenna arrays suffer from the mutual coupling problem between antenna elements, which can critically influence the performance of the array. In this work, a novel and accurate form of compensation matrix is applied to compensate the mutual coupling in a uniform linear array (ULA). This is achieved by applying a new method based on solving a boundary value problem for the whole ULA. In this method, both self and mutual impedances are exploited in an accurate characterization of mutual impedance matrix which results in a perfect mutual coupling compensation method, and hence a very accurate direction of arrival (DOA) estimation. In the new scheme, the compensation ma- trix is obtained by using the relationship between measured voltage and theoretical coupled voltage based on the MOM. Numerical results show that using DOA estimation algorithms to the decoupled voltage obtained by using this method leads to an excellent performance of DOA estimation with higher accuracy and resolution.

The paper presents results of numerical calculations and experimental data on the directional pattern of two 38-element parametric arrays composed of ultrasound sources. Two types of antenna arrays are considered, namely with parallel and coaxial connections of ultrasonic transducers (elements). The results of selecting and functional testing of unit elements are described in this paper. It is found that in the coaxial element connection of the antenna array, the level of side lobes is higher than that in the parallel element connection.

Performance of standard Direction of Arrival (DOA) estimation techniques degraded under real-time signal conditions. The classical algorithms are Multiple Signal Classification (MUSIC), and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT). There are many signal conditions hamper on its performance, such as closely spaced and coherent signals caused due to the multipath propagations of signals results in a decrease of the signal to noise ratio (SNR) of the received signal. In this paper, a novel DOA estimation technique named CW-PCA MUSIC is proposed using Principal Component Analysis (PCA) to threshold the nearby correlated wavelet coefficients of Dual-Tree Complex Wavelet transform (DTCWT) for denoising the signals before applying to MUSIC algorithm. The proposed technique improves the detection performance under closely spaced, and coherent signals with relatively low SNR conditions. Also, this method requires fewer snapshots, and less antenna array elements compared with standard MUSIC and wavelet-based DOA estimation algorithms.

Ever rising increase in number of wireless services has prompted the use of spatial multiplexing through null steering.Various algorithms provide electronic control of antenna array pattern. Simulation-driven technique further introduces correction in array factor to account for array geometry. Taguchi method is used here to combat interference in practical antenna arrays of non-isotropic elements, by incorporating the effect of antenna element pattern on array pattern control in the optimization algorithm. 4-element rectangular and bowtie patch antenna arrays are considered to validate the effectiveness of Taguchi optimization. The difference in the computed excitations and accuracy of null steering confirms the dependence of beam pattern on element factor and hence eliminates the need for extra computations performed byconventional algorithms based on array factor correction. Taguchi method employs an orthogonal array and converges rapidly to the desired radiation pattern in 25 iterations, thus signifying it to be computationally cost-effective. A higher gain and a significant reduction in side lobe level (SLL) was obtained for the bowtie array. Further, due to feed along parallel edges of the patch, the radiating edges being slanted to form the bow shape results in a significant reduction in the area as compared with the rectangular patch designed to resonate at the same frequency.

An intelligent security model for the big data environment is presented in this paper. The proposed security framework is data sensitive in nature and the level of security offered is defined on the basis of the data secrecy standard. The application area preferred in this work is the healthcare sector where the amount of data generated through the digitization and aggregation of medical equipment’s readings and reports is huge. The handling and processing of this great amount of data has posed a serious challenge to the researchers. The analytical outcomes of the study of this data are further used for the advancement of the medical prognostics and diagnostics. Security and privacy of this data is also a very important aspect in healthcare sector and has been incorporated in the healthcare act of many countries. However, the security level implemented conventionally is of same level to the complete data which not a smart strategy considering the varying level of sensitivity of data. It is inefficient for the data of high sensitivity and redundant for the data of low sensitivity. An intelligent data sensitive security framework is therefore proposed in this paper which provides the security level best suited for the data of given sensitivity. Fuzzy logic decision making technique is used in this work to determine the security level for a respective sensitivity level. Various patient attributes are used to take the intelligent decision about the security level through fuzzy inference system. The effectiveness and the efficacy of the proposed work is verified through the experimental study.