This paper proposes a non-overlapping planar cross-arranged ultra-wideband shared-aperture base station antenna array targeting the 2 to 6 GHz application bandwidth. The low-frequency module (double-layer parasitic coupling) and the high-frequency module (chamfered slotted patch) are independently designed, and metal baffles are introduced around the antenna elements to reshape the boundary conditions and physically block the electromagnetic coupling paths. Both simulation and experimental results demonstrate that the fabricated prototype successfully exceeds the targeted 2-6 GHz spectrum, achieving an actual continuous coverage from 1.84 to 6.3 GHz. Specifically, the antenna achieves a gain higher than 5.9 dBi in the measured low-frequency band (1.84-3.72 GHz) and higher than 6.1 dBi in the high-frequency band (3.63-6.3 GHz), with a voltage standing wave ratio (VSWR) below 2 across the entire band. The metal baffles successfully correct the high-frequency radiation pattern distortion and ensure stable directional radiation over the full operating bandwidth. This design provides an efficient, robust, and manufacturable solution for 5G offshore wind power multi-band base station antennas.

As 6G and beyond technologies are stepping into the spotlight, phased arrays are becoming increasingly promising candidates for agile antenna systems. In particular, aperiodic phased arrays provide many desirable traits for such technologies, such as reduced mutual coupling, sidelobe suppression, and grating lobe elimination. However, the design of such systems creates a complex, high-dimensional optimization space due to the competing traits. Traditional optimization methods often fail to scale well when applied to such high-dimensional problems. To this end, three promising algorithms that claim to perform well for such complex and large problems have been identified: Trust region Bayesian optimization (TuRBO), hybrid remora crayfish optimization algorithm (HRCOA), and the zeroth-order optimization toolbox (ZOOpt) featuring a sequential randomized coordinate shrinking classification algorithm (RACOS). The study allows maximal freedom in optimization through using free-floating elements and suggested minimum spacing through weights in the cost function. Two cases of 256 and 625 element arrays, 512 and 1250 variables, respectively, are studied using these three algorithms and compared against the covariance matrix adaptation evolutionary strategy (CMA-ES). The convergence characteristics of each algorithm are analyzed, and their robustness for application in high-dimensional antenna array optimization problems is examined.

We propose a design of 1 × 4 planar antenna array for wideband millimeter-wave (mm-wave) applications, integrated with a metasurface reflector. The single radiating element of the array is composed of a modified ring resonator, designed by combining two rings of different radii. This leads to a compact antenna with dimensions reducing the overall size of the array. For the excitation of array elements, a broadband feeding network is designed, while the wideband characteristics are achieved using a partial ground plane loaded with a square notch. For high gain and improved radiation characteristics, an array of 3 × 10 metasurface unit cells are built and placed at the back side of the antenna array at a specific distance. A prototype of the proposed antenna system is fabricated, and measurements are made to verify the simulated performance. From the results obtained, it is noted that the 1 × 4 planar antenna array with a metasurface reflector offers 12.86 GHz of impedance bandwidth in the range 27.14–40 GHz, and a maximum gain of 12.3 dBi is achieved in the operating frequency range. Furthermore, the directional radiation characteristics are obtained, especially for the low- and mid-band frequencies.

Beamforming plays a central role in enhancing the performance of communication systems; however, suppressing sidelobes in planar antenna arrays (PAAs) while maintaining a compact aperture remains a challenging nonlinear optimization problem. This article presents a two-dimensional (2D) beamforming synthesis framework for PAAs based on the Fractional-Order African Vulture Optimization Algorithm (FO-AVOA), with the objective of minimizing the peak sidelobe level (PSLL) through the joint optimization of amplitude excitations and element placements. The proposed method is benchmarked against established metaheuristic optimizers, including Particle Swarm Optimization (PSO), the Gravitational Search Algorithm (GSA), hybrid PSO–GSA (PSOGSA), the Runge–Kutta Optimizer (RUN), the Slime Mould Algorithm (SMA), Harris Hawks Optimization (HHO), and the baseline African Vulture Optimization Algorithm (AVOA). Simulation results demonstrate that the FO-AVOA, coupled with the proposed 2D formulation, yields superior sidelobe suppression relative to the competing approaches, achieving a lower PSLL with fewer radiating elements, thereby reducing array complexity and overall implementation cost. The obtained results validate the suitability of the FO-AVOA for solving PAA in the context of BFA beamforming and suggest the potential utility of the FO-AVOA for pattern synthesis for other array shapes in various communication systems.

This paper develops a physically consistent precoding framework for extremely large antenna arrays (ELAAs), incorporating structural mutual coupling through a two-dimensional impedance network. To maintain scalability, we introduce a Neumann series approximation for the inverse coupling operator. Our analysis reveals that coupling-aware received power maximization reduces to a Hermitian rank-one quadratic form, whose optimum aligns with the dominant eigendirection of the effective coupling-shaped channel. This result indicates that both eigen-decomposition-based optimization and coupling-aware maximum ratio transmission (MRT) enhance power efficiency under mutual coupling, with the eigenmode design achieving superior performance. In addition, we further extend the analysis from the free-space path to the multipath scenario, demonstrating the robustness and adaptability of the proposed method under practical propagation conditions. Simulations confirm that structural coupling severely degrades conventional MRT, whereas the proposed eigenmode method with Neumann approximated coupling attains the highest received power among all considered schemes. The framework is interpretable, numerically stable, and readily implementable, offering practical guidance for energy-efficient near-field beamforming on ultra-large apertures.

In this paper, a Taguchi-enhanced binary gold rush optimizer (TEBGRO) is proposed for designing thinned antenna arrays with a low peak sidelobe level (PSLL). The method integrates the Taguchi orthogonal experimental design into the population initialization phase, generating high-quality initial populations to improve convergence speed and stability. By combining a differential mutation interference factor and a time-varying transfer function, the algorithm further balances global exploration and local exploitation capabilities. Experimental results show that TEBGRO outperforms other binary optimization algorithms for both 100-element linear arrays and 20 x 10 planar arrays.

Large-scale frames are increasingly used in engineering structures, particularly in aerospace structures. Among them, planar phased array satellite antennas used for global observations and target tracking have received much attention. Considering that structural deformation will degrade the coherence of antennas, a frame with inherent diagonal cables that serves to control the antennas’ static configuration is thoroughly studied. These inherent cables of planar phased arrays are pre-tensioned to preserve the structural integrity and increase the stiffness of the antenna. However, they are also used as actuators in our research; in this way, additional control devices are not needed. As a result, the antenna’s mass will decrease, and its reliability will increase. For high observation accuracy, the antennas tend to be very large. Accordingly, there is a significant deformation of space antennas when they are loaded. For this reason, a nonlinear finite element method is used to consider the structures’ geometrical nonlinearity. In order to achieve shape adjustment, the difference between active and passive cables must be carefully investigated. Furthermore, for the nonlinear structure in this paper, the active cables will deform in tandem with the structure as a whole so that the direction of the active cables’ control forces will also change during the entire control process. This paper elaborates on this problem and proposes a nonlinear optimization method considering this characteristic of the cables. Simulations of a simplified 2-bay and 18-bay satellite antenna are performed to validate the proposed method. Results of the numerical simulation demonstrate that the proposed method can successfully adjust the large-scale antenna’s static shape and achieve high precision.

Distributed vibration control of an on-orbit assembled planar phased array antenna structure

This letter presents a dual-polarized planar phased array antenna incorporating dual-dielectric layers and quasi-defected ground structures loading to enable wide-angle beam scanning. Cylindrical dielectric blocks positioned beneath each dipole element, together with a perforated wide-angle impedance matching layer placed above the array, effectively broaden the active element pattern beamwidth from 55° to 126° while enhancing active impedance matching performance. Quasi-defected ground structures are employed not only to secure the cylindrical dielectric blocks mechanically but also to mitigate surface wave coupling. These structures facilitate a uniform electric field distribution across the array aperture, thereby eliminating parasitic sidelobes. An 8×8 prototype was fabricated and measured. The array achieves ±60° scanning coverage in both principal planes over the frequency range of 2.1–2.5 GHz (17.4% bandwidth), with active VSWR maintained below 2.2 throughout the scan range. Measurement results demonstrate 1.2 dB gain recovery at large scan angles, sidelobe levels suppressed below 8.2 dB, and cross-polarization levels better than –34 dB. The proposed design is modular, scalable, and well suited for applications in radar and wireless communication systems.

ABSTRACT In addressing the pattern synthesis of multiconstraint thinned planar antenna arrays, existing intelligent optimization algorithms encounter limitations such as premature convergence and insufficient solution accuracy. Therefore, we propose an adaptive mutation strategy dung beetle optimizer (AMSDBO) for optimizing thinned planar antenna arrays. The AMSDBO algorithm innovatively constructs a three‐stage collaborative optimization framework, effectively achieving high‐performance design for thinned planar arrays under the constraints of fixed aperture size and sparsity rate through a parameter adaptive adjustment mechanism. Firstly, initial solutions for the dung beetle populations are generated using a chaotic mapping reverse learning (CMRL) strategy to enhance both population diversity and the quality of the initial solutions. Next, the local mutation search (LMS) mechanism is introduced. An adaptive T ‐distribution mechanism is imposed to effectively enhance the early global search capability. Then, the Lévy flight variation strategy is employed to adaptively adjust the positions of the dung beetle population in the later stages, helping the algorithm avoid local optima and accelerating convergence. Simulation results with classical test functions demonstrate that AMSDBO offers significant advantages in convergence accuracy and robustness compared to traditional algorithms (DBO, PSO, and IWO). Additionally, two sets of typical planar thinned array experimental results indicate that the optimization performance of the AMSDBO algorithm is significantly improved compared to traditional optimization algorithms. Specifically, there is a peak sidelobe level (PSLL) reduction of 15.5% for DBO, 11.64% for PSO, and 14.56% for IWO. This confirms the effectiveness and superiority of the AMSDBO algorithm.

This paper proposes a novel angle-of-arrival (AoA) estimation approach for planar antenna arrays with hybrid analog and digital architectures. Although such array structure can significantly reduce system cost and hardware complexity compared to the traditional fully digital arrays, in terms of AoA estimation, the available degree-of-freedom (DoF) is also reduced since the received signals are combined in the analog domain before digital processing, introducing fundamental challenges including angle ambiguity and limited multi-source resolution capability. To overcome these limitations, we propose a two-stage coprime matching estimator that systematically eliminates angle ambiguity through strategic analog beamforming and effectively extracts the exact AoA information even in challenging multi-source scenarios. Furthermore, we derive the closed-form expression of the Cramér-Rao lower bound (CRLB) for two-dimensional AoA estimation in planar hybrid arrays, providing a theoretical performance benchmark that accounts for both azimuth and elevation angles. Numerical simulations demonstrate that our proposed approach achieves superior multi-source resolution and estimation accuracy compared to state-of-the-art methods, while asymptotically approaching the CRLB.

The following paper presents an application of the principle of collapsed distributions to the diagnosis of square grid planar antenna arrays. The principle states that each azimuthal cut of a planar array pattern (array factor), with phi = phi _o, is equivalent to the pattern generated by a linear array. The linear array is obtained by projecting all of the excitations of the planar antenna on to the line phi = phi _o. This idea is used to develop an algorithm for detecting faulty elements in damaged planar arrays, where only on-off faults are considered. The algorithm uses far-field complex samples of the damaged pattern taken along the phi = 0^{circ }, 45^{circ }, 90^{circ } cuts. It uses this information to perform an exhaustive search to find the three collapsed linear arrays (in the specified directions) that best match the samples of the damaged pattern. Thus, the coordinates of the faulty elements along the three mentioned axes can be easily obtained. The algorithm was applied here to the diagnosis of a 76-element square grid antenna with circular boundary and quadrantal symmetry.

ABSTRACT This letter presents a low‐profile, wideband, polarization‐insensitive frequency selective rasorber (FSR) designed to reduce the radar cross section (RCS) of high‐gain planar antenna arrays. The proposed structure consists of a lumped resistor‐based lossy top layer and a lossless bottom layer, separated by an air gap. It achieves high absorptivity (> 90%) across 3.8–7.85 GHz and 9.67–13.4 GHz, while maintaining an in‐band transmission at 8.5 GHz with an insertion loss of 0.9 dB. The fourfold symmetric and compact topology ensures polarization insensitivity and angular stability up to 50° incidence. The FSR is integrated with a planar microstrip patch antenna array, effectively reducing its out‐of‐band RCS under X‐polarization and both in‐band and out‐of‐band RCS under Y‐polarization, without affecting in‐band transmission. Both the standalone FSR and the integrated antenna system have been fabricated and measured, demonstrating up to 10 dB RCS reduction over a 111% fractional bandwidth under normal incidence.

A New Dual-Band Dual-Circularly Polarized mmWave Planar Array Antenna Based on Novel Compact Diplexing Double-C-Shaped Elements

ABSTRACT A hybrid algorithm which combines Invasive Weed Optimization (IWO) and Grey Wolf Optimizer (GWO) is used into the synthesis of the subarray division of the planar array antennas. The GWO is combined with IWO. After several iteration of IWO, the GWO is executed to improve global search capability and avoid local optimal point. The proposed algorithm fully exploits the advantages of both IWO and GWO, thereby improve the optimization performance. In order to maximize the beam collection efficiency (BCE) and minimize the peak sidelobe level outside the receiving area (CSL), the whole array antenna is divided into several subarrays. The positions of array elements, subarray structure, and excitation amplitudes of each subarray are optimized. The proposed method can constrain the minimum adjacent element spacing, the element number of each subarray, and the size of the array antenna simultaneously. Simulation examples show that the proposed algorithm can get better synthesis results. Compared with other literatures, higher BCE and lower CSL are achieved. The effectiveness and feasibility of the proposed method are demonstrated.

Hybrid synthesis approach for enhanced sidelobe suppression in linear and planar antenna arrays

We present autocorrelation matching method as a phase-only synthesis method to design power pattern of both linear and planar antenna arrays. Equating the autocorrelation coefficients of an array having a presumed amplitude of antennas to those of a previously designed amplitude-phase array forms the basis of this method. Considering certain examples, the effectiveness of the proposed method for both linear and planar arrays has been verified. Received: August 4, 2025Revised: September 5, 2025Accepted: October 16, 2025

This letter presents an optimization method for the design of a shaped-beam antenna array (SBAA) based on the method of maximum power transmission efficiency, addressing the limitations of traditional beamforming techniques in flexible pattern synthesis. The proposed approach enables the efficient generation of various far-field flat-top patterns according to practical requirements through a far-field optimization process. By configuring an SBAA as transmitting and deploying several virtual test antennas in the far-field region as receiving, the optimal excitation distribution is analytically derived by maximizing power transmission efficiency under an equal constraint on the received power. To validate the proposed method, a 4×4 SBAA along with a radio frequency circuit capable of providing adjustable amplitude and phase excitation, was designed, fabricated and tested. The feasibility of generating three types of flat-top radiation patterns—including square, circular, and annular shapes—has been demonstrated through both simulations and experimental measurements. The measured results show that the effective flat-top coverage for both the square and circular patterns spans the angular range from –30° to 30°, with the gain fluctuation maintained below 1 dB. The proposed design offers a flexible and time-efficient approach for precise flat-top beam shaping, making it suitable for deployment in 5G/6G base stations and indoor communication systems.

In this communication, a new sampling method called knowledge-based sampling method (KBSM) is proposed for deep learning (DL)-assisted planar antenna array design. This approach uses active-based-element-modeling (ABEM) combined with KBSM. KBSM optimizes the dimensionality and volume of training data. Consequently, this method improves the adaptability of DL model for various antenna array topologies, and significantly reduces the time-consuming data requirements for training while maintaining high accuracy in predicting the active element patterns (AEPs). Through full-wave simulation, the proposed approach demonstrates superior accuracy with reduced data requirements. Additionally, the practical applicability of the approach is validated through the fabrication and measurement of a 2.45 GHz patch antenna array. This study presents a robust framework for efficient and accurate design of planar antenna arrays, addressing the challenges of mutual coupling and edge effects.

Automotive radar is known as a promising sensing technology in autonomous vehicles due to its reliability. In current autonomous vehicles, the 77 – 81 GHz frequency band is the principal operating band for automotive radars. For the efficient operation of automotive radars, the radar antenna needs to be highly accurate. However, higher operating frequencies may present challenges in radar antenna design, requiring high gain, wide bandwidth, and low sidelobe levels (SLL). To address this issue, this study aims to adapt a planar series-fed linear antenna array to 79 GHz automotive radar applications using three different grounded coplanar waveguide (GCPW) feed configurations, including coplanar gap source port, vertical ground bridge, and wave port. Simulations were conducted to evaluate the performance of the antenna with the feed configurations. According to the results, it was shown that the antenna with wave port feed achieved the best impedance bandwidth (>3 GHz), whereas the antenna with either the coplanar gap source port or the vertical ground bridge configurations exhibited better main lobe phase centering and a higher gain (>18.4 dBi), with an acceptable SLL below -16.28 dB. It is believed that these findings may contribute to the development of high-performance radar antennas for next-generation autonomous vehicles.