In this article, a hybrid inversion algorithm based on an innovative stochastic algorithm, namely, the bat algorithm (BA) is proposed. Electromagnetic inverse scattering problems are ill-posed and are often transformed into optimization problems by defining a suitable cost function. As typical methods to solve optimization problems, stochastic optimization algorithms are more flexible and have better global searching ability than deterministic algorithms. However, they share a common disadvantage: heavy computing load. This directly restricts the application of the algorithms in high-dimensional problems and real-time imaging environments. To solve this issue, diffraction tomography (DT) is introduced to provide a reference for the initialization of the BA. Furthermore, the hybrid method makes full use of the complementary advantages of linear reconstruction algorithms and stochastic optimization algorithms to improve accuracy and efficiency at the same time. Moreover, in order to avoid the algorithm falling into local extrema, a linear attenuation strategy of the pulse emission rate is proposed to enable more bats to perform global search in the early stage of the algorithm. In the numerical experiments for different types of dielectric objects, the reconstruction results of this hybrid BA-based algorithm are compared with those of the DT and the particle swarm optimization (PSO).
A numeric-analytical solution of a problem concerning an impedance vibrator with local asymmetric excitation is derived in the thin-wire approximation. Solution correctness is confirmed by satisfactory agreement of numerical and experimental results from well-known literary sources. Based on the optimization modeling, the design of the impedance antenna characterized by three resonant frequencies intended for mobile communications operating in GSM 900, GSM 1800, and WiMAX ranges is developed. The analysis of basic electrodynamic characteristics of the vibrator antenna has proved the possibility of practical applications of this antenna for phones, portable radio stations, electronic gadgets, and base stations.
Radar data collected on two sides of a horizontally dissipative layered medium are required to invert for the medium parameters. The two-sided reflection and transmission responses are reduced to two single-sided reflection responses. One is the measured dissipative medium response, and the other is the reflection response of the corresponding effectual medium, which has negative dissipation. Marchenko-type equations are solved using these two reflection responses. The obtained focusing functions in the dissipative and effectual media are used to invert for the permittivity and the permeability under the assumption of weak dissipation in reflection. Once these parameters are known, the travel times are used to estimate the layer thicknesses. Finally, the focusing functions are used to estimate the conductivity in each layer. The method does not require any model information and runs as a fully automated process. A numerical example shows that the method works well for a horizontally dissipative layered medium. Statistical analysis for several noise models shows that the method is robust at least up to 40 dB additive and multiplicative white noise.
This paper describes a U-net based Deep Learning (DL) approach in combination with Subspace-Based Variational Born Iterative Method (SVBIM) to provide a solution for quantitative reconstruction of scatterer from the measured scattered field. The proposed technique can be used as an alternative to conventional time consuming and computationally complex iterative methods. This technique comprises of a numerical solver (SVBIM) for generating the initial contrast function and a DL network to reconstruct the scatterer profile from the initial contrast function. Further, the proposed technique is validated against theoretical and experimental results available from the literature. Root Mean Square Error (RMSE) value is used as the metric to measure the accuracy of the reconstructed image. The RMSE values of the proposed method show a significant reduction in the reconstruction error when compared with the recent Back Propagation-Direct Sampling Method (BP-DSM). The proposed method produces an RMSE value of 0.0813 against 0.1070 in the case of simulation (Austria Profile). The error value obtained by validating against the FoamDielExt experimental database in the case of the proposed method is 0.1037 against 0.1631 reported for BP-DSM method.
This paper investigates the effect of an external plane wave on a Multi-conductor transmission line (MTL) located above a multilayer soil directly in the time domain. An improved finite-difference time-domain (FDTD) method is used, in conjunction with the Vector Fitting (VF), to obtain the recursion relations of voltages and currents along the line by discretizing the equations in time and one-dimensional space. The source terms of the coupling equations are efficiently obtained in the time domain based on the Gaver-Stehfest algorithm. An equivalent model is also established in this work, where the geometry with three conductors is reduced to two conductors. Finally, some examples are presented to illustrate the effect of the soil and the plane wave on the transient.
A coplanar waveguide (CPW) fed multiple-input multiple-output (MIMO) ultra-wideband (UWB) antenna with high isolation and dual band-notched characteristic is proposed. The antenna consists of two orthogonal circle patches. An annular SRR slot and a rectangular SRR slot are added on the patches to produce two notched bands. High isolation is successfully acquired by adopting a double Y-shaped branch between the two radiation elements. By cutting the fractional substrate, the antenna size has been reduced by 31.4 percent. The measured results show that the working bandwidth of the antenna covers 2.36-12 GHz, and at the same time, the notched bands cover 3.37 GHz-3.98 GHz and 4.71 GHz-5.51 GHz. The isolation is better than 21 dB. The paper also studies the radiation pattern, peak gain, and envelope correlation coefficient (ECC) of the UWB MIMO antenna.
Owing to its all-day and all-weather imaging capabilities, high-resolution spaceborne synthetic aperture radar has shown great potential for the effective monitoring of wide-area, ultra-high-voltage (UHV) transmission lines. Scattering characteristics of UHV power lines in 3-m-resolution TerraSAR-X images is analyzed in this paper. First the study area and structure of the UHV transmission line are introduced. Then, the data processing method is described, which includes the preprocessing of TerraSAR-X images and target feature extraction. Finally, the scattering characteristics of the UHV power line are analyzed, and the analysis results demonstrate that the UHV power line can be visible in a TerraSAR-X image only when the angle between its extension direction and the azimuth of the sub-satellite ground track is within ±15°. Furthermore, besides the span length, the spatial location of the UHV power line in a TerraSAR-X image is also influenced by the angle between its extension direction and the azimuth of the sub-satellite ground track, as well as by the height difference between adjacent pylons.
Modern combat teams face an increasingly complex battlefield, where threats may arise from a number of different sources. Examples include not only conventional attacks through rocket propelled grenades but also improvised explosive devices and weaponised unmanned aerial vehicles. Combat teams can now be equipped with sophisticated surveillance and reconnaissance capability, as well as automatically activated defences. The focus of this paper is to consider the utility of collaborative active protection systems, which are designed to provide an active defence against threats to a combat team. Specifically, a general statistical framework for the analysis of such systems is introduced, with a particular focus on high power radio frequency directed energy weapon countermeasures. The mathematical model allows for a subset of the combat team to be responsible for target detection and tracking, and a time-varying subset of team members with suitable countermeasures to be specified separately. The overall probability of threat defeat and team survivability is then derived. Some examples are provided to investigate the utility of such systems.