Antenna Array Synthesis Research Articles

Lineer Anten Dizilerinin Fizik Tabanlı AOA, CryStAl ve LA Algoritmaları ile Sentezi

In this article, 10, 16, and 24-Element of Linear Antenna Arrays (LAAs) synthesis are carried out with 3 different novel physics-based metaheuristic methods. These methods are called Archimedes Optimization Algorithm (AOA), Crystal Structure Algorithm (CryStAl), and Lichtenberg Algorithm (LA). In order to prevent electromagnetic interference from other systems operating in the same frequency band, the Sidelobe Level (SLL) of the radiation patterns of the LAA has been suppressed as much as possible. While performing the LAA synthesis, Half Power Beam Width (HPBW), which is related to the directivity of the antenna, is also taken into account. The methods proposed in this study are run independently 30 times to obtain the statistical values of LAA synthesis. The minimum, maximum, median, and standard deviation values of the SLL and HPBW of the radiation patterns obtained as a result of these runs are tabulated. The performances of these three proposed novel physics-based optimization methods are given comparatively. In all simulation studies, the CryStAl method generally showed the best performance.

Synthesizing of concentric circular antenna arrays by using a combination of ant lion optimizer and sequential quadratic programming

AbstractAntenna array synthesis is quite a popular topic in electromagnetics and finding suitable array parameter values is a challenging nonlinear engineering problem in this field. In recent years, it has been realized that optimization algorithms can be used to achieve desired solutions in this area. Besides, improvements in the optimization algorithms make it possible to perform synthesis processes on different array structures and to obtain better results. In this paper, a method based on a combination of ant lion optimizer (ALO) and sequential quadratic programming (SQP) is proposed for the concentric circular antenna array (CCAA) synthesis. Excitation amplitudes of array elements are optimized for CCAAs with low maximum sidelobe level (MSL), narrow first null beamwidth (FNBW), and low dynamic range ratio (DRR). The results of proposed ALO‐SQP method are compared with those of 11 different algorithms: ALO, moth flame optimizer (MFO), SQP, symbiotic organisms search (SOS), biogeography based optimization (BBO), opposition‐based gravitational search algorithm (OGSA), cat swarm optimization (CSO), firefly algorithm (FA), evolutionary programming (EP), backtracking search optimization algorithm (BSA), and seeker optimization algorithm (SOA). The comparisons indicate that the CCAAs synthesis using the proposed method presents good MSLs, FNBWs, and DRRs.

A Novel Design of Flat-Top Beamforming Anti-Multipath Antenna

This article discusses a novel design method of wide-beam circular polarization array antenna for satellite navigation. For special applications such as satellite navigation guiding aircraft landing, high-performance ground reference station antennas are required. In the system of satellite navigation guiding aircraft landing, the antenna of satellite navigation receiver needs to have the following radiation characteristics: the shape of antenna pattern is close to an ideal hemisphere, the upper half of space has uniform right-hand circular polarization gain, and the beam has the characteristic of sharp cutoff below 5 degrees of elevation. Whether the GNSS reference station antenna can have a wider beam circular polarization characteristic to receive more navigation satellites signal; whether it can suppress the multipath effect to a greater extent to reduce the multipath error; and whether it can work in a wider frequency band, so that several major satellite navigation systems work together, the above factors directly affect the satellite navigation and positioning accuracy of the entire system. The beam of this antenna has the following feature: sharp cutoff near the horizon for multipath mitigation at low elevation angles. Comprehensive design thereby accelerates system design. It owns wide beam, good circular polarization characteristics, low elevation angle sharp cutoff, and ultralow sidelobe radiation characteristics that achieve the purpose of receiving satellite navigation signal and multipath. The low sidelobe characteristic of the antenna is beneficial to suppress multipath effect. According to the theoretical knowledge of the symmetrical dipole and the four-arm helical antenna, the simple structure of the symmetrical element is fully utilized, and the printed balun easily realizes the dual-frequency operation of the antenna. Combined with the wide-beam circular polarization characteristic of the four-arm helical antenna structure, the shaped beam array antenna is designed. The wide-beam circularly polarized antenna unit not only covers the frequency band of the satellite navigation system but also satisfies the system performance and key feature requirements of the array antenna for the unit; that is, it satisfies the wide-beam circular polarization characteristics of the upper half space. According to the linear array basic theory and array antenna synthesis theory, Woodward Lawson sampling synthesis algorithm is used to synthesize the array amplitude and phase weights corresponding to the specific antenna pattern required for the Ground-Based Augmentation System (GBAS) engineering. The shaped beam array antenna consists of 21 units, of which 11 antenna units are directly fed, and the feeding ports of the rest are dummy ports. It is an equally spaced array antenna. The spacing between antenna units is close to half wavelength. They are fed according to the value corresponding to the excitation function. The array antenna is simulated by HFSS (High-Frequency Structure Simulator). Compared with traditional satellite navigation antennas, the antenna in this paper has excellent front-to-rear ratio and flat-top beam pattern. The results show that the wide-beam circularly polarized array antenna meets the engineering requirements of GBAS applications and lays the solid foundation for GBAS engineering applications.

Design and synthesis of circular antenna array using artificial hummingbird optimization algorithm

Design and synthesis of circular antenna array using artificial hummingbird optimization algorithm

Constant modulus shaped beam synthesis via linear fractional semidefinite relaxation

Excitation amplitude control is a critical issue regarding the shaped beam synthesis of array antennas. Ideally, excitations can have the same amplitude, and the desired beam can be achieved only by changing the phases. This method is called constant modulus synthesis, which can reduce the complexity of array antennas and is more conducive to the feeding, but it is really difficult to realize. In this paper, the authors derive a novel constant modulus beam synthesis algorithm, which uses the linear fractional semidefinite relaxation to relax the constant modulus constraints. Simulation results show that this method is stable and can maintain the excitation modulus while realizing the shaped beam.

Advanced Marine Predator Algorithm for Circular Antenna Array Pattern Synthesis.

The pattern synthesis of antenna arrays is a substantial factor that can enhance the effectiveness and validity of a wireless communication system. This work proposes an advanced marine predator algorithm (AMPA) to synthesize the beam patterns of a non-uniform circular antenna array (CAA). The AMPA utilizes an adaptive velocity update mechanism with a chaotic sequence parameter to improve the exploration and exploitation capability of the algorithm. The MPA structure is simplified and upgraded to overcome being stuck in the local optimum. The AMPA is employed for the joint optimization of amplitude current and inter-element spacing to suppress the peak sidelobe level (SLL) of 8-element, 10-element, 12-element, and 18-element CAAs, taking into consideration the mutual coupling effects. The results show that it attains better performances in relation to SLL suppression and convergence rate, in comparison with some other algorithms for the optimization case.

Effect of chaos factor in radiation pattern in planner antenna arrays with chaos adaptive invasive weed optimization

For mobile <span>communication and spatial detection of antennas should have high directive radiation pattern, in this context pattern synthesis of planar circular antenna arrays is highly significant such design has been done inverse weed optimization. The basic objective e is to study invasive weed optimization in compression with modified chaotic adaptive invasive weed optimization. The focus of the study is the effect of chaotic factors suitable for sinusoidal mapping for chaos as applicable to the context of the design of antennas. Taking various numbers of elements of the antenna and the distance between the antenna’s radiation patterns are studied by varying chaos factors through MATLAB programming. It is found that the critical point of 2.3 for chaos factor makes the map enter into phase of chaos prior to the critical point is a phase of periodicity starting with chaos factor of 2. Below this value there is no chaos but a phase of convergence. These phases are useful having a trade of convergence and chaos. By varying the factor of chaos the impact on the radiation factor of non-uniform planar antennas has been found to give phases of convergence of chaos which are essential for making trade of between exploitation and exploration required in optimization.</span>

Synthesis of Concentric Circular Antenna Array Using Whale Optimization Algorithm

Through the ages the importance of the swarm intelligence-based algorithm has gained popularity in the field of optimization. The Whale Optimization Algorithm (WOA) is one such popular meta-heuristics nature inspired swarm intelligence-based algorithm which is well accepted for solving optimization problems, as it is simple and capable to obtain optimal results efficiently. In this paper, few benchmark functions along with radiation patterns of concentric circular antenna array are presented and their performance is optimized using WOA. Simulation results are shown by taking various benchmark functions, namely: Three hump & Six hump camel function, Ackley, Egg Crate Function, and Egg Holder Function. The capability of the WOA algorithm is also tested through pattern synthesis with respect to the thinned array as well as non-uniformly excited array for four diverse sets of CCAA geometries. When comparison is being done with respect to renowned and most popular optimization approaches like PSO, the WOA technique proves to be excellent in terms of maximum SLL suppression. Optimization results show the better capability of WOA in the field of optimization.

Machine Learning-Assisted Array Synthesis Using Active Base Element Modeling

Array synthesis under practical constraints is a vital design task. Traditional array synthesis methods usually deal with isolated antenna elements without considering mutual coupling (MC) or mounting-platform effects, which results in unacceptable degradation in practical array designs. An efficient machine learning-assisted array synthesis (MLAAS) method is introduced using efficient active base element modeling (ABEM). This method greatly extends the boundaries of practical antenna array synthesis from the perspectives of both accuracy and design freedom. Using much fewer samples than those in conventional MLAAS methods, all possible element designs are accurately modeled into one active base element (ABE). Compared with conventional active element pattern (AEP)-based methods, the ABEM aims to predict AEPs for elements with arbitrary allocations and electromagnetic (EM) surroundings, therefore offering more degrees of freedom for practical array designs. Four array design examples are used to verify the effectiveness of the proposed method.

Synthesis of Antenna Arrays with Parasitic Elements for Interference Rejection using a LMS Method

The objective of this paper is to design a parasitic antenna array capable of rejecting interfering signals and directing its main lobe towards the wanted signal. The designed antenna is a linear array consisting of an active monopole and fourteen parasitic monopoles. The method used is LMS, making it possible to calculate the values of the reactive loads to be connected to the ports of the parasitic elements so that the radiation patterns satisfies the fixed constraints. The simulation results in CST-MWS (Computer Simulation Tool Microwave Studio software) of the radiation patterns show an energy level of less than -0.71 dB in the direction of the interference and a gain greater than 5 dB in the direction of the wanted signal. Thus, this technique will make it possible to design directional antennas, with low energy consumption and interference rejection.

Branching of solutions of the nonlinear equations arising in the problems of synthesis of the plane antenna arrays

Branching of solutions of the nonlinear equations arising in the problems of synthesis of the plane antenna arrays

Phased Antenna Array Synthesis Technique Employing Special Directional Patterns and Demonstrating Improved Performance

Antenna arrays with special, in particular, cosecant directional patterns are widely applied in the current radio engineering systems. When synthesizing antenna array using well-proven techniques, the expected directional pattern is set, with rare exceptions, to the zero values outside the cosecant sector. At the same time, this approach to the directional pattern development is not optimal. It is proposed to supplement the template of the expected directional pattern with the two linear slopes and a constant level area equal to the pattern maximum. A technique for optimizing geometric parameters of the template according to the criterion of the minimum standard deviation of the synthesized directional pattern from the ideal cosecant pattern has been developed. For this deviation, certain restrictions are presupposed: on the magnitude of the maximum pattern deviation in the cosecant sector or/and on the level of side lobes. The method for synthesizing an antenna array by decomposing the directional pattern into Nyquist-Shannon-Kotelnikov series is used while optimization technique is implemented based on the genetic algorithm. The results of the technique approbation show that the use of the optimized template makes it possible to improve the quantitative characteristics of the antenna array directivity. In particular, for the 70° cosecant sector and the 12-element array, a 4 dB gain in maximum pattern deviation is achieved with a simultaneous decrease in the maximum side lobe level by 3 dB. The developed technique can be used for synthesizing a phased antenna array with the directional pattern different from the cosecant one.

Linear Antenna Array synthesis using Rao and Jaya algorithms

Optimization algorithms are being widely applied in real-time applications. In recent times, Jaya and Rao algorithms have been prominent. The performance of these algorithms will be analyzed for the objective function. The results thus obtained are more accurate and fast compared to previous algorithms. Also, Jaya and Rao algorithms will be utilized for linear array antenna synthesis for the arrays that are equally spaced. Therefore it is of present interest to evaluate the performance of linear antenna array using these algorithms.

Synthesis of Mask-Constrained Pattern-Reconfigurable Nonuniformly Spaced Linear Arrays Using Artificial Neural Networks

In this article, a novel multibranch encoder-decoder-based artificial neural network (ANN) framework is proposed for pattern-reconfigurable nonuniformly spaced linear array synthesis. In the proposed framework, different encoder–decoder branches are devoted to synthesizing different radiation patterns to satisfy the desired radiation patterns. In each encoder–decoder branch, the encoder, and the decoder serve as the array synthesizer and analyzer, respectively. By minimizing a suitably-defined loss function with respect to multiple radiation patterns, element amplitudes, and positions, not only multiple mask-constrained radiation patterns can be successfully achieved, but also the common element amplitudes and positions with minimum inter-element spacing control can be obtained. Thus, different radiation patterns can be switched by phase-only control. In addition, by using different training samples, the proposed method can consider the ideal synthesis of the array factor, as well as the actual synthesis of antenna arrays to consider the mutual coupling effects in the synthesis process. Simulation results are provided to validate the capability, efficiency, and attractiveness of the proposed method.

Unequally Spaced Antenna Array Synthesis Using Accelerating Gaussian Mutated Cat Swarm Optimization

Low peak sidelobe level (PSLL) and antenna arrays with high directivity are needed nowadays for reliable wireless communication systems. Controlling the PSLL is a major issue in designing effective antenna array systems. In this paper, a nature inspired technique, namely accelerating Gaussian mutated cat swarm optimization (AGMCSO) that attributes global search abilities, is proposed to control PSLL in the radiation pattern. In AGM-SCO, Gaussian mutation with an acceleration parameter is used in the position-updated equation, which allows the algorithm to search in a systematic way to prevent premature convergence and to enhance the speed of convergence. Experiments concerning several benchmark multimodal problems have been conducted and the obtained results illustrate that AGMCSO shows excellent performance concerning evolutionary speed and accuracy. To validate the overall efficacy of the algorithm, a sensitivity analysis was performed for different AGMCSO parameters. AGMCSO was researched on numerous linear, unequally spaced antenna arrays and the results show that in terms of generating low PSLL with a narrow first null beamwidth (FNBW), AGMCSO outperforms conventional algorithms.

Meta‐heuristic optimization algorithms for placement of multiple nulls and minimization of side lobe level in quadrant symmetric sparse array antenna

SummaryThe optimization of the non‐uniform planar array antenna parameter in order to minimize the signal interference in the electromagnetic environment through null placement is one of the most important areas of investigation in the field of wireless communication. This study deals with an effective method of synthesis of a quadrant symmetric sparse planar array antenna using the novel implementation of the well‐known meta‐heuristic optimization algorithms, namely, symbiotic organism search (SOS) and moth flame optimization (MFO) algorithms. The objective of this work is to place multiple small and wide nulls at the desired angles and simultaneously minimize the side lobe levels using a nonlinear mathematical approach. Three examples are presented with constraints that include the inter‐elemental distance, fixed number of array elements in the aperture, and the aperture size. The radiating antenna array elements are considered to have fixed uniform current distribution. The meta‐heuristic optimization approach offers the advantages of avoiding the infeasible solution while finding the best optimal set of element positions to reduce side lobe level in the desired radiation pattern. The radiation pattern characteristics and the computation time associated with each example and each algorithm are recorded and compared for arriving at the conclusion. The superiority of SOS is found in terms of the optimized side lobe levels. At the same time, both algorithms are found to be efficient in positioning the symmetric nulls in desired locations in the radiation pattern successfully. When compared with the published papers, proposed approach yields better results confirming the effectiveness of the performance of these algorithms.

Linear Antenna Array Synthesis by Modified Seagull Optimization Algorithm

This paper presents a study of linear antenna array (LAA) synthesis with a seagull optimization algorithm (SOA) to achieve radiation patterns having low maximum sidelobe levels (MSLs) with and without nulls. The SOA is a new optimization technique based on the moving and attacking behaviors of the seagull in the nature. In this study, the original mathematical model of SOA is modified by compensating the exploration and exploitation features to improve the optimization performance. The optimization ability of the modified SOA (MSOA) is tested with seven numerical examples of LAA. In the first three examples, the amplitude values of the array elements are optimized by MSOA whereas the element position values are calculated by MSOA for the last four examples. The numerical results obtained by MSOA are compared with those of different algorithms from the literature. The results reveal that MSOA algorithm is very good at optimizing antenna array parameters to obtain a desired radiation pattern. Additionally, it is seen that MSOA finds better results than the compared algorithms in terms of MSL and single and multiple null depth levels (NDLs). The contribution of the modification of MSOA is shown with a convergence curve to compare with the original one.

Development of antenna system for use in meteorological and climatic control complexes

The synthesis of a cylindrical antenna array for ground-based mobile weather monitoring complexes, based on quadrifilar radiators, is considered. The basic mathematical expressions for determining the electrodynamic characteristics of both the radiator from the antenna array and the AA itself are presented. Various phenomenological models of these radiators are considered. The approach to the synthesis of phenomenological models of the radiator and antenna array as a whole is described. The results of such synthesis are given, and the main characteristics and values of DG, CG, SWR, RP for the given type of radiator and AA in the corresponding frequency range are obtained. Techniques for using phenomenological models for operational synthesis of electrodynamic structures such as cylindrical AA and quadrifilar radiator are developed and described in detail. The possibility of applying this approach to the synthesis of this type of structures for radar weather monitoring systems is shown.

Thinned array antenna synthesis using modified binary particle swarm optimization with minimization of sidelobes

PurposeThe purpose of this paper is to propose radiating system by avoiding electromagnetic interference in unwanted directions and to radiate the energy in the required direction with an optimization technique.Design/methodology/approachPractically, multiple, incompatible variables require concurrent boost on a synthesis of systematic antenna assemblage. The authors have worked out the main statistic penalty function to ensure all the restrictions. Here, MBPSO (Modified Binary Particle Swarm Optimization) is developed and introduced thin planar synthesis restriction. The sigmoid function is used to update the particle position. Different analytical demonstrations have been carried out, and the exhibited methods are predominant than the algorithms.FindingsA 20 × 10 planar antenna array is synthesized using modified BPSO. The authors have suppressed the PSLL in two principal planes and as well as in the entire f plane. Numerical results state that MBPSO outperforms the other binary BPSO, BCSO, ACO, RGA, GA optimization techniques. MBPSO achieved a −51.84 dB PSLL level, whereas BPSO achieved −48.57 dB with the same 50% thinning.Originality/valuePlanar array antenna formation is one of the most complex syntheses because the array gets filled with more antenna elements. The machine-like complication and implementation of such an antenna arrangement with a broad opening would be expensive. It is not easy to control the required radiation patterns shape by using a uniform feeding network. To get better flexibility for sustaining the sidelobe levelheaded along with consistent amplitude distribution. So as far as prominence has been given to the evolutionary algorithm, find an ideal solution for objective array combinational problems.

Shaped beam synthesis via semidefinite relaxation (SDR) based on magnitude least squares (MLS)

Shaped beam synthesis of array antennas has attracted the attention of many researchers in recent years and has been widely used in many scenarios. In the previous methods, finding the feasible solution with beam pattern mask constraints has been applied widely, but the solution may not exist with an improper mask. Besides, if the array size is large, the dimension of solution is high, which causes the solution procedure slow. In this study, from the perspective of the magnitude least squares (MLS) model, combined with the semidefinite relaxation (SDR) technique, a new beam pattern synthesis algorithm is derived. The MLS model can guarantee that the solution always exists and can reduce the dimension of solution via introducing auxiliary variable and non-uniform angular sampling. Simulation results show that this algorithm is effective, can approximate the main lobe well and obtain lower side lobes in contrast to the reference method.