International Journal of RF and Microwave Computer-Aided Engineering最新文献

Antenna systems with more complicated geometries have been created as a result of evolving technology and rising performance standards in the industry. The geometric complexity of modern antennas makes it difficult for circuit theory tools or parametric studies to produce adequate findings, making it difficult for designers to create the designs they want. Even though full-wave electromagnetic (EM) modeling tools are widely utilized today, they are computationally expensive for local optimization alone. In order to speed up the stages of the simulation-based design of high-performance systems, many strategies have been devised to solve and/or minimize this challenge. Thanks to their adaptability, affordable computing costs, and widespread usage, surrogate-based models have grown to be a well-known branch. Herein, an innovative knowledge-based methodology for building a coplanar waveguide (CPW)-fed antenna using surrogate models is presented. In this work, a knowledge-based methodology using surrogate modeling is applied as an advanced approach that combines domain-specific knowledge with surrogate models to optimize the performance of a microwave antenna in a computationally efficient manner. For this aim, firstly, a 3D-EM simulator is deployed to generate a dataset for a deep learning-based surrogate model. When compared to the conventional optimization approach using direct deployment of EM simulators which is around 47.2 h, the proposed surrogate model approach has an average cost reduction of over 50% which corresponds to a total computational time of 24.3 h. The collected results are compared to performance metrics for prototype antenna designs as well as simulated outcomes from EM simulators and counterpart works from the literature.

A sixteen-port circularly polarized (CP) ultrawideband (UWB) multiple-input−multiple-output (MIMO) belt antenna is designed and developed for wireless body area network (WBAN) applications. The proposed antenna comprises sixteen modified octagon-like ring antenna elements with a common ground. These antenna elements are designed on leather material and can be worn as a belt. Each antenna element contains a microstrip line feed and a modified octagon-like open-ended ring radiator to generate circular polarization. The belt antenna provides an impedance bandwidth (S₁₁ ≤ −10 dB) of 3.08–11 GHz (112.5%) and a 3 dB axial ratio bandwidth (ARBW) of 4.7–7.07 GHz (40.27%). The envelope correlation coefficient (ECC) amongst the resonating elements is <0.003. Additionally, the bending analysis and specific absorption rate (SAR) of the presented antenna are examined. The overall size of the belt antenna is 30 mm × 574 mm × 1 mm. The designed belt antenna is suitable for WBAN applications due to its leather material, good on-body performance, and nearly identical simulated and experimental results.

In this article, an improved nonlinear model for gallium nitride high-electron-mobility transistors (GaN HEMTs) is proposed. Aiming at the problem of insufficient accuracy of the nonlinear DC model caused by the self-heating effect and trap effect in the traditional model, this thesis uses the Softplus function to improve the traditional nonlinear DC model and establishes a nonlinear DC model including the self-heating effect, which is verified by the three GaN HEMT devices of different sizes. The MSE of I_ds is less than 2.44 × 10⁻⁶. The traditional empirical basis model needs to calculate the partial derivative of the current expression with respect to V_ds, which is tedious and complicated. The proposed model can be directly used to fit the G_m. The verification results show that the MSE of the G_m is less than 1.07 × 10⁻⁴, which proves the effectiveness of the equation.

With the continuous development of the radar field, millimeter-wave radar target detection, as a major tool, faces important challenges in improving detection performance. Especially in some application scenarios, due to multitarget interference and other reasons, the detection performance of the traditional variability index (VI) constant false alarm rate (CFAR) (VI-CFAR) algorithm decreases significantly in the case where both side windows contain interfering targets. To solve this problem, this paper introduces an innovative algorithm, Kullback–Leibler Divergence and Otsu’s Method Enhanced VI-CFAR (KLOVI-CFAR), to better adapt to the multitarget background environment. By combining the KL scattering and Otsu method, we realize the adaptive rejection of outliers in the reference window and further automatically select the detection algorithm adapted to the processed background environment. The results of simulation experiments verify the excellent detection performance of KLOVI-CFAR in multitarget environments with interfering targets in both side windows. The algorithm not only effectively improves the detection capability and antijamming but also shows good detection performance in homogeneous environment and clutter edge cases. The research results in this paper provide a useful reference for improving the radar target detection algorithm.

Multiport network model (MNM) of microstrip patch antennas is an extension of cavity model analysis. In MNM, electromagnetic fields present under and outside patch are modeled separately and the patch is considered as a planar element with multiple ports at its edges. The MNM approach was previously used for the analysis of different patches such as rectangular and circular. However, MNM analysis for irregular-shaped hexagonal patch antenna is not studied yet. Analysis of hexagonal patch antenna is required for its several advantages over other patches such as equivalent surface current distribution with less size compared to circular patch and higher bandwidth. In this work, the irregular-shaped hexagonal patch antenna is analyzed using MNM technique. The antenna is decomposed into rectangular and right-angle triangular segments. Multiport impedance (Z) matrices are calculated for all elements based on Green’s functions of corresponding shapes. Finally, the current distribution of the complete patch is obtained by connecting these elements using Z matrices. The irregular-shaped patch antenna is fabricated, and its responses are measured to verify the results obtained from MNM analysis. MNM can estimate antenna performance with ~3.5% average error with respect to simulated responses in terms of antenna performance parameters.

This paper presents radio frequency energy harvesting (RFEH) using a rectenna system for 3.1 and 5.75 GHz frequencies. The antenna used in this work is a Vivaldi antenna with a new structure. Mounting the newly designed parasitic element on the proposed Vivaldi antenna has improved the gain and directivity of the antenna. The parasitic element is introduced as the director element. The arms of the director element are expanded exponentially. We simulated the proposed antenna design in CST Studio Suite and simulated the proposed rectifier in an advanced design system (ADS). The substrates chosen for the antenna and rectifier are of low-cost type. We have used the voltage doubler technique for the rectifier. Good impedance matching using two stubs has made it possible to connect the rectifier to the antenna. We obtained RF to DC measurement results for the proposed design, which are 56.3% for 3.1 GHz at 8.5 dBm input power and 33.4% for 5.75 GHz at 6.5 dBm input power, respectively. After combining the antenna and the rectifier, the maximum efficiency measured for the power input of 5 dBm at the frequency of 3.1 GHz is equal to 50.8%, which is suitable for energy harvesting.

Machine learning-assisted electromagnetic simulation has become an effective acceleration tool for designing microwave components by introducing high-precision models and optimization algorithms, featuring fast design and high efficiency. However, enormous amount of data generated from the blind preliminary and computationally expensive simulation is required to predict the accuracy response. An efficient geometric parameter optimization method for microstrip bandpass filter (BPF) based on a one-dimensional convolutional neural network is proposed. Nonlinear convergence factor, adaptive weight, and Gaussian difference mutation strategies are integrated using the whale optimization algorithm to avoid the local optimum and improve optimization accuracy. Computational efficiency is improved significantly with small-scale training data. The validity and efficiency of the proposed method are confirmed by fifth-order microstrip BPFs, and the performance of the predicted structure parameters is significantly improved, which shows great promise for application in optimization and performance improvement in microwave electromagnetic simulation.

A miniaturized high-performance metasurface (MTS) antenna with cross-shaped strips is designed, which can be applied to wireless communication systems. The resonant frequency of the main mode of the proposed MTS is reduced by embedding a 2 × 2 cross-shaped strip array in the gaps of the 3 × 3 circular MTS array, resulting in a lower operating frequency and miniaturization. The main mode of the MTS and the probe mode are excited simultaneously by the L-probe structure, resulting in a dual-mode resonance for a broadband performance. The entire design mechanism of the antenna is explained analytically through characteristic mode analysis (CMA) method. Additionally, the cross-polarization levels in H-plane are effectively suppressed by a metal via positioned at the MTS center. Measured results show a wide impedance bandwidth of 32.6% (reflection coefficient ≤ −10 dB) with an MTS size of 0.44λ₀ × 0.39λ₀ (where λ₀ is the free-space wavelength of 6.6 GHz). The achieved peak gain is 7.1 dBi, with a 2 dB gain bandwidth of 36% (5.25-7.55 GHz) and a low cross-polarization level below -20 dB.

Electromagnetic cloaking with monitors within waveguide plays a pivotal role in minimizing the risk of detection while intercepting sensitive information which holds immense potential in both military and communication sectors. However, the integration of electromagnetic cloaking and monitoring is challenging and even more difficult to realize in waveguide. To address these challenges, we propose a metadevice design method based on the internal multiport method (IMPM) for ensuring effective monitoring while maintaining electromagnetic cloaking in the complex environments of waveguide systems. Strategically adjusting the distribution and arrangement of auxiliary scatterers in proximity to the monitoring apparatus can flexibly regulate the behavior of electromagnetic wave propagation to enhance the cloaking performance of metadevice. The cases presented in the paper validate the designed metadevices that are capable of achieving both cloaking and monitoring for monitors within waveguide systems.

The design of a rocket-borne data transmission system is presented in this article. This data transmission system is used for Meridian Space Weather Monitoring Project II sounding rocket. The major function of this data transmission system is to transmit payload data and rocket telemetry data to ground station. The data transmission system achieves power greater than 4 W (36 dBm). The amplitude unbalance is 1.60% (0.14 dB) and the phase unbalance is 1.74°. Total power consumption of the data transmission system is less than 24 W (28 V power supply). The radiation performance of the data transmission antenna is good. Based on the actual condition of solid rocket, the relevant heat dissipation and vibration reduction measures are designed under the demand of miniaturization. The data transmission system has been tested by performance test, environmental simulation test, system integration test, and other tests; the test results show that it has good working performance, good stability, and high reliability.