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

The domain decomposition method (DDM) enables efficient simulation of electromagnetic problems in large-scale array antennas using full-wave methods on moderate hardware. This paper introduces and compares two nonoverlapping DDMs serving as preconditioners with outstanding simulation efficiency. The first method targets finite periodic array antennas by transforming a single array unit rather than explicitly modeling the entire array, effectively leveraging repetitive structures to significantly reduce memory usage and computation time. The second method applies to universal array antennas with arbitrary geometries, employing both planar and nonplanar mesh-based domain partitioning at subdomain interfaces for flexible modeling of complex arrays. To further enhance computational performance, we propose a parallel multilevel preconditioner based on the block Jacobi preconditioner, thereby accelerating the solution efficiency of subdomain matrix equations in both methods. Additionally, since the choice of domain partitioning method significantly impacts the computational efficiency of DDMs, we propose three different subdomain partitioning strategies. These strategies enable us to accelerate computations while expanding our capacity to simulate a wider variety of types of cases. We developed a fast electromagnetic radiation simulation tool utilizing these techniques. Simulations of exponentially tapered slot (Vivaldi) antenna arrays and antenna arrays with radomes demonstrate that our tool achieves accuracy comparable to commercial software, and notably, our tool outperforms commercial software in terms of the speed of iterative solutions.

In this paper, a new coating structure is proposed for broadband radar cross section (RCS) reduction using 1-bit metasurfaces. The designed structure consists of two types of unit cell, arranged in concentric square rings. The substrate of unit cells is different, FR4 and Ultralum-2000 with thicknesses of 2.4 and 0.762 mm, respectively. The proposed structure shows an ultrawideband property to reduce the RCS, less than −10 dB, in the frequency range of 14–45 GHz. This range covers part of Ku-band (14–18 GHz), K-band (18–27 GHz), and Ka-band (27–40 GHz) and part of millimeter-wave band (40–45 GHz). To validate the designed work and simulation results, a prototype with the dimension of 84 × 84 mm² is fabricated and tested. Also, the RCS reduction is determined analytically and presented. The measured results verify well the analytical and simulation results. In short, this work includes three new points: (1) the use of two substrates with different thickness and dielectric constant to design unit cells, (2) a new arrangement of array cells in the form of concentric square rings, and (3) achieving a great bandwidth to reduce RCS.

The use of surrogate models in assisting evolutionary algorithms for antenna optimization has achieved significant research outcomes. The construction of surrogate model primarily depends on two aspects; one is the selection of datasets, and the other is the model’s structure and performance. This paper proposes a novel dataset selection method aimed at enhancing the performance of the constructed surrogate model. Additionally, based on Bayesian neural network (BNN) and leveraging the advantages of handling sequence data with long short-term memory (LSTM), a BNN-LSTM surrogate model is introduced. After training, this surrogate model is used as the fitness evaluation function, enabling optimization design based on differential evolution (DE) algorithm. Experimental validations are conducted using the optimizations of a dual-frequency slotted patch antenna and a rectangular cut-corner ultrawideband antenna as examples. Results demonstrate that the proposed surrogate model exhibits high accuracy, providing a guidance for antenna optimization.

A spaceborne Earth-coverage phased array (ECPA) antenna at Ka-band is proposed for low-Earth orbit (LEO) satellite applications, which is based on digital beamforming (DBF) partially shared subarray architecture to implement two stages of DBF. By taking into account the effects of mutual coupling in active element pattern optimization, a new method to obtain an Earth-matched beam of the equivalent element of the ECPA is presented, in which the DBF-shared subarray, segmental shaping technique, and differential evolution algorithm are utilized to achieve Earth-coverage characteristic for the ECPA. Both the design method and the principle of DBF partially shared subarray for grating lobe suppression are presented. Moreover, a 16-element DBF-shared subarray with a shared ratio of 4:1 obtaining an Earth-matched beam pattern is designed, optimized, and verified by full-wave simulation in Ansys Electronics Desktop. Taking the DBF-shared subarray as the equivalent element, an ECPA including 40 DBF-shared subarrays is also designed and simulated. Numerical results demonstrate that the proposed ECPA has excellent performance of Earth-coverage scanning to compensate for the satellite communication link variation caused by path loss variation during beam scanning for LEO applications. In addition, the ECPA has the advantages of a low sidelobe level better than −20 dB as well as grating lobe suppression.

A wideband high-efficiency dual-polarized metal-only reflectarray antenna is designed and analyzed. The unit cell is composed of a layer of grooved metal plate and a ground, with an air layer in the middle. The proposed element features a phase range of about 360° and works independently in orthogonal directions, enabling dual linearly polarized operations. Based on this unit cell, a circular array including 177 elements with a diameter of 250 mm is simulated and fabricated at 10 GHz. The measured results show that the reflectarray exhibits a good performance in both horizontal and vertical polarizations, with a 1-dB gain bandwidth of 20.2% and 20% and peak aperture efficiency of 62.3% and 61%, respectively. In addition, sidelobe and cross-polarization levels are also satisfactory.

This work provides a comprehensive review of conjugately characteristic impedance transmission lines (CCITLs) and their applications in quarter-wave–like transformers (QWLTs). These promising concepts are employed in the development of miniaturized CCITL-based power dividers (CCITL-PDs). A thorough design procedure for CCITL-PDs with arbitrary power division ratios is presented, including detailed derivations and analysis of the perfect isolation condition. For illustration, an equal-split CCITL-PD implemented using multisection transmission lines (MSTLs) is designed to achieve a 25% reduction in electrical length compared to conventional equal-split Wilkinson power dividers. Although the achieved reduction is modest, this example provides valuable insights and approaches for further optimizations in CCITL-PD design, showcasing its potential for microwave component miniaturization.

A compact low-profile dual-band dual-polarized wearable patch antenna, capable of working in 2.4 and 5.8 GHz ISM band for either on-body or off-body applications with different radiation patterns in each working band, is presented in this paper. The fabricated antenna consists of four layers including modified ground and patch layers and two dielectric layers made of jean fabric, and it has a radius of 30 mm with overall height of 3.4 mm fed by a single probe. The proposed structure is designed in a way that is capable of radiating linearly polarized (LP) waves in lower working frequency and circularly polarized (CP) waves in its upper working band. The ground plane is modified to ensure the dual-band radiation as well as miniaturization of the antenna. The patch of the antenna benefits from truncated corners and four circular stubs which are practically coupled with antenna’s modified ground to provide desired axial ratio and dual polarization capability. With the help of computer-based simulations, the antenna is placed on human body tissue and the calculated amount of SAR values in each band for 1 g tissue is 0.15 and 0.89 Wkg, respectively, which guarantee the safety of the human body in close proximity to the antenna.

In this paper, deep learning–based data-driven surrogate modeling approach is proposed for enhancing cost-efficiency of multiband antenna design optimization. The proposed surrogate model–assisted design approach has achieved a computational cost reduction of almost 40% compared to the conventional direct electromagnetic solver–based design methodologies in case of single design example. As for the validation of the proposed method, the obtained optimal design parameters from the surrogate model are used to manufacture an antenna design. The obtained results from the experimental measurement are compared with counterpart results from the literature.

A novel and simple design method of wide-passband filters with wide stopband based on half-wavelength (λ/2) resonators coupled by a short connected line (SCL) is proposed and analysed in this paper. Different from the traditional parallel-coupled structure filters, SCL is proposed to realize a strong coupling between two adjacent resonators and suppress the parasitic passbands simultaneously. And the eigenmode analysis method and impedance ratio characteristics are both used to reveal the mechanism of wide-stopband implementation. To further expand the stopband, filters based on step-impedance resonators (SIRs) with SCL are proposed and analysed in detail. To verify the proposed design method and wide-stopband filtering structures, three 4-pole filters with uniform-impedance resonators (UIRs), SIRs with same impedance ratio, and SIRs with different impedance ratios are designed, fabricated, and measured. The proposed filters can realize a wide stopband up to 5.8f₀ with rejection level better than 20 dB. Moreover, the proposed filters can easily realize a wide bandwidth.

Passive millimeter–wave (PMMW) scanners are widely used for personal security screening in public places due to their nonradiation and high real-time capabilities. However, the images obtained by these scanners frequently exhibit low signal-to-noise ratios and contrast, presenting challenges for automated detection systems. To address this issue, we propose an efficient semantic segmentation approach, FA-UNet, that employs a UNet architecture with a fusion attention mechanism to conduct binary classification (human body vs. background, including objects) for PMMW images. This approach incorporates a spatial attention mechanism into the lateral connections between the encoder and decoder and introduces a channel attention mechanism during the feature fusion process in the decoder. By combining these attention mechanisms, FA-UNet leads to more precise segmentation outcomes. The segmented image is then fused with the original image using our multistage fusion method, in which, first, the two images are blended in a 1:1 ratio for object detection. Then, a new fused image is obtained by adjusting the ratio within a certain range (0.3–0.5). Finally, the object detection results are overlaid on this fused image to generate a directly displayable image. We evaluate our method using a self-made dataset. Experimental results demonstrate that FA-UNet can accurately segment the human body region and preserve object shapes effectively. Using the fused image for object detection helps reduce false detections caused by background noise interference while improving the detection rate of weak targets. Additionally, the fused image aids in manual image interpretation in locations with higher security inspection levels and contributes to protect the privacy of individuals undergoing inspection to the greatest extent possible.