This paper presents a novel design methodology for the design and optimization of a miniaturized multiband microstrip patch antenna (MPA) suitable to be used in wireless communication systems. Two design steps were used to do that. In the first step, an initial antenna is designed by a trial and error approach to nearly operated in the desired frequency bands, but the level of impedance matching (S11<-10 dB) for one or more bands is unsatisfactory, or some bands are uncovered by the antenna. Then, the second design step is beginning after that aiming to achieve optimized antenna by applying an optimization algorithm to effectively fine-tune the impedance matching of the initial deigned antenna to closely satisfy all the desired frequency bands. As an illustrative example, the proposed optimization methodology was used for designing a miniaturized multiband MPA suitable for operating at five different frequency bands, 915 MHz (RFID band), 1850 MHz (GSM band), (ISM-Industrial, Scientific, Medical), 2.45 and 5.8 GHz, and 3.5 GHz (WiMAX band). The proposed MPA used here is composed of two patch structures printed on both sides of an FR4 substrate occupying an overall size of just 28×28 mm2. The final optimized antenna is fabricated, and its simulated and measured results were coinciding with each other validating the design principle. Moreover, simulation antenna performance parameters, surface current distribution, realized peak gain, and efficiency besides the radiation patterns at the desired frequency bands are obtained using CST MWS.
A revision of main propagation mechanisms of radio waves for wireless sensor networks is presented in this paper. In order to address this topic, the free space model is firstly taken as a reference. Classical concepts like ground reflection, diffraction, and surface waves are included from a theoretical point of view, and some aspects related to wireless sensor networks are analyzed for each subject. A key parameter is the height of antennas which plays an important role on distinct formulations like reflection coefficient of the ground surface. From there, when antennas are very close to ground surface, the far field conditions could be different from that typical expression. Hence, some of propagation models involve a characterization of far field conditions, and practical settings of antennas for wireless sensor networks are analyzed by electromagnetic simulation. Attenuation due to vegetation is also reviewed, and models suitable for these networks are exposed.
We present a rigorous solution of a two-dimensional problem of stationary electromagnetic plane wave diffraction by a slot in a perfectly conducting screen having finite thickness in the presence of a plane dielectric layer behind the screen. For obtaining this solution, the method of additive regularization of singularities for field diffraction integrals is developed. This method is suitable for the cases of transparent, absorbing and amplifying dielectric. It reduces to explicit extraction of singularities in the form of supplementary singular integral terms, which describe waveguide modes of a dielectric layer. On the bases of the obtained solution, the conditions of optimum diffraction excitation for such modes are investigated in dependence of geometrical parameters of the problem for the cases, when these parameters are of the order of the radiation wavelength.
The classification algorithms of polarimetric synthetic aperture radar (PolSAR) imagesare generally composed of the feature extractors that transform the raw data into discriminative representations, followed by trainable classifiers. Traditional approaches always suffer from the hand-designed features and misclassification of boundary pixels. Following the great success of convolutional neural network (CNN), a novel data-driven classification framework based on the fusion of CNN and superpixel algorithm is presented in this paper. First, the region-based complex-valued network utilizes both the intensity and phase information to predict the label of each pixel and constructs the label map based on spatial relations. Second, superpixel generating algorithm is adopted to produce the superpixel representation of the Pauli decomposition image, and the contour information which reflects the boundary of each category is preserved. Finally, the original label map and contour information are fused to make the decision of each pixel, outputting the final label map. Experimental results on public datasets illustrate that the proposed method can automatically learn the intrinsic features from the PolSAR image for classification purpose. Besides, the fusion of the superpixel features can effectively correct the misclassification of the boundary and singular pixels, thus achieving superior performance.
The failure risk of electronic equipment submitted to an electromagnetic aggression may be seen as the conditional probability that the susceptibility level of equipment is reached, knowing that a given constraint is applied. This paper focuses on the estimation of the probability density function of the susceptibility level of equipment. Indeed, the production variability of electric/electronic equipment under analysis implies that its susceptibility level may be considered as a random variable. Estimation of its distribution through susceptibility measurements of a limited set of available equipment is required. Either a Bayesian Inference (BI) or a Maximum Likelihood Inference (MLI) may be used for assessing the most probable density function. Above all, we highlight that they have to be used to delimit a set of probable distribution functions rather than the most probable one. It then provides realistic bounds of the failure probability at a given test level. First both types of inference are carried out on theoretical distributions. Then we compare the two methods on a virtual piece of equipment whose distribution is not known a priori but can be estimated a posteriori. Finally, we apply these inferences on a set of actual susceptibility measurements performed on several copies of equipment. We check that for extremely small sample size (a dozen) the Bayesian approach performs slightly better. However, above around 40, the two methods perform similarly. In all cases, the likelihood estimations provide a clear statement of the probabilistic estimation of the statistics of susceptibility level given a limited sample of pieces of equipment.
Stochastic wave equations are derived to describe electromagnetic wave propagation in an isotropic medium in which the electric permittivity and the magnetic permeability are weakly-random functions of time. Approximate analytical solutions are obtained using separation of variables and the WKB method for some configurations that can be used to model the electromagnetic field in the ionosphere. The form of the initial and boundary conditions determines whether the solution takes a form representing a direct current electric field or continuous pulsation electromagnetic waves. The temporal variation of the calculated induced electromotive force (EMF) is in agreement with observations.
This paper studies the power transfer characteristics of a resonator array for inductive power transfer by means of the accurate analytical solution of its circuit model. Through the mathematical inversion of a tridiagonal matrix, it is possible to obtain closed-form expressions for the current in each resonator and consequently expressions for the power transfer and efficiency of the system. The method can be applied to a resonator array powering a load at the end of the array or a receiver facing the array at any position. With the expressions obtained, it is possible not only to achieve a better understanding of the power transfer characteristics in resonator arrays but also to obtain the conditions for maximum power transfer or maximum efficiency, for several conditions and parameters of the system. A prototype of a stranded-wire resonator array powered by a resonant inverter, capable of delivering power to a load from 65 W to 90 W with efficiency values between 63% and 88%, was built in order not only to validate the expressions obtained but also to show their practical applicability and demonstrate that these arrays can be used for higher power transfer applications.
Miniature Air Launched Decoy (MALD) is an electronic warfare technique for inducing an angular deception in a monopulse radar by recreating glint angular error. MALD flies cooperatively with the true target, forms unresolved group targets within the radar beam, and destroys the detection, tracking and parameter estimation of monopulse radar for the true target. In this paper, a typical scenario for one target and one decoy was discussed, and the measurement model of target and decoy based on the actual non-ideal sampling conditions was established. The joint multi-targets probability density was adopted to dynamically describe the number and state of the targets within the radar beam. Based on the original observation without threshold decision, a joint detection and tracking algorithm for unresolved target and decoy was proposed under the Bayesian framework, and the judgment of existence of jamming and the target state estimation were deduced. Simulation results showed that the proposed method enabled quick detection of the appearance of MALD and estimated the state of target with minimal delay and high precision. Stable tracking of the true target was achieved under severe jamming conditions.
We present an optimization procedure for wireless power transfer (WPT) applications and test it numerically for a WPT system design with four resonant circuits that are magnetically coupled by coaxial coils in air, where the magnetic field problem is represented by a fully populated inductance matrix that includes all magnetic interactions that occur between the coils. The magnetically coupled resonators are fed by a square wave voltage generator and loaded by a rectifier followed by a smoothing filter and a battery. We compute Pareto fronts associated with a multi-objective optimization problem that contrasts: 1) the system efficiency; and 2) the power delivered to the battery. The optimization problem is constrained in terms of: 1) the physical construction of the system and its components; 2) the root-mean-square values of the currents and voltages in the circuit; and 3) bounds on the overtones of the currents in the coils in order assure that the WPT system mainly generates magnetic fields at the operating frequency. We present optimized results for transfer distances from 0.8 to 1.6 times the largest coil radius with a maximum power transfer from 4 kW to 9 kW at 85 kHz, which is achieved at an efficiency larger than 90%.
In this paper, we obtain an asymptotic solution for the problem of electromagnetic diffraction at a thick curved dielectric layer with a nonuniform dielectric permittivity. We show that, in the case of thick layers, the main asymptotic approximation already comprises the curvature correction, verify the results by comparison with a solution obtained with the integral equation method, and offer to approximate the piecewise constant dielectric permittivity of a stratified layer with a continuous function.