Antenna Array Synthesis Research Articles

Time‐modulated multibeam steered antenna array synthesis with optimally designed switching sequence

SummarySteering the radiation pattern of an antenna array towards the desired spatial angle is beneficial for modern‐age communication systems. The generation of multiple steered patterns by enhancing the first‐order harmonics of a time‐modulated antenna array (TMAA) with controlled radiation features is proposed in this paper. Suitable switching sequences are designed to realize an efficient electronic beam steering with these simultaneously generated narrow directional beam patterns. TMAAs are considered the time‐domain counterparts of phased arrays where high‐speed switches are used to achieve a weighted response by periodically modulating the array elements instead of attenuators or phase shifters. This periodic modulation inherently produces spurious harmonic patterns generally considered as power loss in unintended directions. The beam steering aimed in this paper is accomplished by exploiting the first‐order harmonic patterns in some specific directions keeping the fundamental pattern unaltered. The intended first positive and first negative harmonic components of the TMAA are utilized as steered multibeam patterns, whereas all the remaining harmonic components are suppressed to improve the efficiency of the array. To achieve this, suitable switching sequences are designed by optimizing the ON‐time duration and switching intervals of the elements with a wavelet mutation‐based particle swarm optimization (PSOWM). 16‐element linear TMAA is used to generate the desired patterns with low sidelobe levels (SLLs) for enhanced performance. Numerical results obtained for spatially independent steered patterns are presented and compared with the state‐of‐the‐art literature results.

Cat Swarm Optimization Algorithm For Antenna Array Synthesis

Cat swarm optimization (CSO) is a developmental technique enlivened by the animals in Mother Nature for taking care of optimization issue. Short of what multi decade after CSO is proposed, it has been improved and applied in various fields by numerous scientists as of late. CSO is created by noticing the practices of cats, and made out of two sub-models, i.e., following mode and looking for mode, which model upon the practices of cats. The prerequisite of high directivity signal with extremely quick pillar guiding is preposterous by a solitary antenna. This imperative is aid by staged array antenna which is a mix of various little antennas that can create shaft with high directivity with quick electronic pillar guiding. The radiation example of an antenna array relies firmly upon the weighting technique and the math of the array. The issues related with pillar design causing high obstruction in communication which confine them use by and by. To beat these im-pediments, optimization innovation called Cat Swarm Optimization are applied in mix with the old style array blend strategies for staged array combination. An optimization issue is determined whose arrangement yields an ideal array for stifling impedance because of high side lobe level and grinding lobe. Results are introduced for ideal arrays of shifting array calculation, with various number of antenna components, and for distinct beamwidths and scan angles.

A Dynamic Invasive Weeds Optimization Applied to Null Control of Linear Antenna Arrays with Constrained DRR

In the present work, a dynamic stochastic method is proposed and used for the synthesis of uniform linear antenna arrays. The proposed method combines the classical invasive weeds (IWO) and the mutation process, which makes it robust, simple and shows flexibility to be adapted. The dynamic IWO applies the mutation process in the calculation of standard deviation during the spatial dispersal process of produced seeds while keeping the mean at the parent plants. In the mutation process, if special conditions were achieved, the standard deviation would be re-initialized. This proposed method tries to achieve an optimal array pattern by acting on the relative amplitude excitation of each element in the linear array for an optimal inter-element spacing. The optimal array pattern has deep or broad nulls in some directions of interferences with low sidelobes level. The objective of the synthesis is to get amplitude excitations with low dynamic range ratio (DRR), which facilitates the design of beamforming feed network. To illustrate the robustness of the proposed method, numerical examples are presented and compared with the obtained results using bees algorithm (BA), bacterial foraging algorithm (BFA), real genetic algorithm (RGA), and the corresponding reference array pattern for each example.

An Effective Artificial Neural Network-Based Method for Linear Array Beampattern Synthesis

The beampattern synthesis of antenna array is always known as a computationally cost task that needs efficient strategies to deal with. In this article, a novel artificial neural network (ANN)-based array synthesis method is proposed. By establishing an encoder–decoder-based ANN framework, the mask-constrained beampattern in terms of focused or shaped beam for linear arrays with arbitrary given array geometry is successfully synthesized. More in detail, the encoder serves as an array synthesizer, while the decoder behaves as an array analyzer. Thanks to the designed pretrained decoder, such an approach is computationally efficient so that real-time array synthesis can be potentially achieved. Moreover, the proposed method allows one to consider both ideal and actual linear arrays with mutual coupling effects and nonidealities. The results of a wide numerical validation involving amplitude-only, phase-only, and amplitude–phase excitation syntheses are presented to assess the flexibility and the versatility of the proposed method also in comparison to the competitive state-of-the-art synthesis techniques.

The Method for the Constructive Synthesis of Planar Antenna Arrays with Consideration of the Interelement Coupling

The method for the constructive synthesis of planar antenna arrays (AAs) based on the neural network approach with consideration of interelement coupling is proposed. Within the AA mathematical model, it is assumed that when substantiating the AA configuration, antenna elements can be divided into groups of active, unused, or passive elements with the currents induced by neighbor elements. The structure of a neural network including a classifying neural network and several approximating networks is substantiated. The learning algorithm for the neural network is divided into two stages: the stage of a separate pre-tuning of each part of the neural network and the stage of joint training of all its parts. We have obtained the solution to the problem of the constructive synthesis of AA according to the requirements for the shape of the radiation pattern. The solution confirms the method workability and good prospects of the neural network approach.

Gaussian Approach for the Synthesis of Periodic and Aperiodic Antenna Arrays: Method Review and Design Guidelines.

This paper presents a complete overview of the recently developed Gaussian approach for the synthesis of both periodic and aperiodic linear antenna arrays in conjunction with an exhaustive numerical investigation of the achievable performance. The position and excitation synthesis problems are jointly modeled to enable a direct mutual comparison between the two strategies. To this aim, different parameter settings are selected to analyze the results in terms of achieved beamwidth and maximum sidelobe levels as a function of the array aperture and of the number of radiating elements. The insights inferred from this numerical investigation are exploited to derive a novel first-step procedure with the purpose of enabling an antenna engineer to quickly identify the most suitable design approach, thus reducing the time required for antenna system development.

ADMM-based array antenna synthesis algorithm with reconfigurable pattern element selection

The paper considers the array beam pattern synthesis (BPS) problem with reconfigurable pattern elements (RPE). Both the array weight and the array pattern are optimized, which further suppresses the peak sidelobe level (PSLL) compared with the fixed pattern array. For the array pattern optimization, the conventional selecting of appropriate N elements from K radiation patterns requires to evaluate all possible KN choices, resulting in the non-deterministic polynomial-hard RPE selection problem. In this work, this problem is solved through investigating different element pattern combinations with randomly arranged pattern locations. In such way, the possible solutions to the RPE selection problem has an overall choices of CN+K−1K−1=(N+K−1)!N!(K−1)!, which extremely shrinks the solution space. An algorithm with the RPE selection and array weight optimization is proposed for the BPS problem. Furthermore, the alterative direction method of multipliers (ADMM) framework is introduced to accelerate the computation speed. The proposed algorithm provides an effective scheme for generating appropriate RPE combinations for PSLL suppression, resulting in a wider-angular scanning ability for array antenna. Simulation results demonstrate 0 dB to 4 dB lower PSLL can be obtained compared with the algorithms based on the fixed element pattern.

Three‐phase adaptive differential evolution for antenna array synthesis

AbstractAntenna array synthesis is a complex nonlinear optimization problem. Differential evolution (DE) is an efficient method to solve the problem of antenna array synthesis. Different mutation strategies applied in different evolutionary phases can improve the search ability of DE. In this paper, a three‐phase adaptive differential evolution (TADE) algorithm is proposed for antenna array synthesis problems. In TADE, the evolution process is divided into three phases according to the population fitness distribution and iterative information, namely, the initial phase, the stable phase, and the precise phase. Based on statistical information of population fitness values, a suitable mutation strategy of each phase is designed for enhancing the optimization performance. The performance of the TADE algorithm is verified by a CEC 2013 test suite, three circular antenna array problems, and a planar antenna array problem. The results show that the TADE algorithm achieves better performance in solving antenna array synthesis than several advanced DE variants and some non‐DE global optimization algorithms.

The Concentric Elliptical Antenna Array Patterns Synthesis Using Marine Predators Algorithm

In this paper, the pattern synthesis of concentric elliptical antenna arrays (CEAAs) for effective antenna design is presented. The current amplitudes and angular positions values of the CEAA elements are optimally found by using the Marine Predators Algorithm (MPA) in order to obtain the optimum radiation pattern. The MPA method is a novel nature-based optimization algorithm that is inspired by ocean predators foraging strategy. The antenna arrays with reduced maximum side lobe levels (MSL) and narrowed half power beam widths (HPBW) are an efficient antenna with optimum radiation pattern to suppress interference and increase directionality. In addition, CEAAs with different numbers of elements are examined to show the flexibility and performance of the proposed algorithm in this study. For 18-element CEAA, MPA obtained the HPBW between 29.18° and 31.34°, and MSL between − 20.70 and − 25.89 dB. For 30-element CEAA, the optimum values of HPBW are between 20.13° and 21.38°, and the optimum values of MSL are between − 18.90 and − 20.50 dB. The results of pattern synthesis obtained by MPA are compared with other metaheuristic optimization methods, and it is seen that the results of the proposed method are generally better.

Optimum design of linear and circular antenna arrays using equilibrium optimization algorithm

AbstractIn this paper, equilibrium optimization algorithm (EOA), which is a novel optimization algorithm, is applied to synthesize symmetrical linear antenna array and non-uniform circular antenna array (CAA). The main purpose of antenna array synthesis is to achieve a radiation pattern with low maximum side lobe level (MSL) and narrow half-power beam width (HPBW) in far-field. The low MSL here is an important parameter to reduce interference from other communication systems operating in the same frequency band. A narrow HPBW is needed to achieve high directionality in antenna radiation patterns. Entering the literature as a novel optimization technique, EOA optimally determined the amplitude and position values of the array elements to obtain a radiation pattern with a low MSL and narrow HPBW. The EOA is inspired by models of the control volume mass balance used to predict equilibrium as well as dynamic states. To demonstrate the flexibility and performance of the proposed algorithm, 10-element, 16-element and 24-element linear arrays and eight-element, 10-element and 12-element CAAs are synthesized. The MSL and HPBW values of radiation pattern obtained with the EOA are very successful compared to the results of other optimization methods in the literature.

Directional pattern of an antenna array with non-equidistant arrangement of receiving elements

This article presents an analysis of the directional pattern of an antenna array with a non-equidistant arrangement of receiving elements. This problem is relevant for the synthesis of antenna arrays with the required location of zeros and maxima in the radiation pattern. The analysis is suitable for obtaining an analytical expression describing the directional pattern of a flat phased antenna array, the receiving elements of which are located on the antenna curtain.

Design of aperiodic spherical antenna arrays for wideband performance

This paper illustrates a highly nonlinear problem related to the design of aperiodic antenna arrays using spherical geometry for maximum performance. This synthesis of aperiodic spherical antenna arrays considers two design cases: (1) aperiodic arrays with a nonuniform spacing between rings assuming equal element spacings on the same ring (ASANRUE case) and (2) aperiodic arrays with a nonuniform spacing between rings and between antenna elements of the same ring (ASANRNE case). This process is carried out by using the differential evolution (DE) optimization technique with the goal of finding the optimum angular position of each element on the elevation and azimuthal planes to achieve the maximum performance in terms of the side lobe level, directivity, and number of antenna elements used in the array for three design objectives: natural response of the radiation pattern, beam scanning, and the restriction of a minimum distance among elements. The innovative contribution of this paper is the application of the differential evolution algorithm to a nontrivial and highly complex design problem: the aperiodic element distribution over a spherical antenna arrangement. The advantage of this approach with respect to the state of the art on the topic of spherical array design is that a lower side lobe level and maximum directivity for a spherical antenna array can be obtained for aperiodic element distributions with a reduced number of antenna elements and hence a smaller radius, which means less complexity and lower fabrication costs. Simulation results based on CST Microwave Studio are provided to take mutual coupling into account.

An optimal time modulated compact circular antenna array design using a stochastic optimization technique

ABSTRACT This paper presents a time modulated far-field radiation pattern synthesis of a compact circular antenna array (CAA) by employing a stochastic optimization technique known as grey wolf optimization (GWO). The compactness of the antenna array is achieved by reducing the inter-element distances between the elements of the array which leads to the miniaturization of the antenna array size. On the other hand, an optimal far-field radiation characteristic is achieved by suppressing the side lobe level (SLL) as well as by narrowing the first null beamwidth (FNBW). A lower SLL value is necessary to avoid the interference with the system working in the same frequency, whereas, a narrow FNBW helps the antenna array to attain a high directivity. The performance of a time modulated antenna array (TMAA) depends on the rise on–off time, pulse shape as well as on the switching time duration of each element of the array which radiates at different harmonic frequencies. In this paper, the generation of radiation pattern at the fundamental/central frequency and its first two harmonic frequencies are considered for the design issue.

A New Beamforming Technique for the Synthesis of Uniform Circular Antenna Arrays Using Reduced Number of Antenna Elements

The number of elements reduction in different antenna array configurations such as linear, circular, rectangular, planar, and non-planar is of main concern for several research groups. This minimizes the complexity of the feeding network in static antenna arrays, whereas, in adaptive antenna arrays, it reduces the number of active components. The main issue in the array synthesis is to preserve the radiation pattern with minimum distortion compared to the original pattern. These issues are addressed by many researchers in linear, planar, and concentric circular arrays, but no attempt is made in the synthesis of uniform circular antenna arrays (UCAAs) that have elements distributed on a single circle. This is because the synthesis is almost performed in one plane where the radiation patterns in other planes are not predicted. In this paper, most of the aforementioned challenges are treated; the number of elements is reduced, the radiation pattern has minimum distortion, and the radiation pattern is symmetric in all array orthogonal planes. This is performed by dividing the original UCAA's 3D radiation pattern into a suitable number of 2D plane patterns, each of which is separately synthesized using the specified number of elements. The 2D pattern synthesis process for a particular plane is confined to estimating a new set of non-uniform excitation coefficients while keeping the original UCAA's array radius. To construct the final set of synthesized excitation coefficients for the 3D array pattern synthesis, we aggregate all of the estimated sets of excitation coefficients and take the average. To verify the efficacy of the proposed technique, the original and synthesized arrays are realized using the CST Microwave Studio using λ\mathord / \vphantom λ2 2 dipole elements. The results indicated that substantially matched patterns were obtained. Furthermore, the coupling between the synthesized array elements is decreased, which enhances the radiation efficiency and realized array gain.

A novel hybrid IWO and CS algorithm for phase-only pattern synthesis of large array antenna

In this paper, a novel hybrid Invasive Weed Optimization (IWO) and Cuckoo Search (CS) algorithm (IWO/CS) is presented for phase-only pattern synthesis of large array antenna. The hybrid IWO/CS algorithm embeds the Levy flight of CS algorithm into IWO algorithm as a global guide, thereby enhancing the global search ability of the algorithm. At the same time, in order to avoid trapping into the local optimal solution, mutation operator is introduced to enhance search ability of the algorithm. Finally, competitive exclusion operation is improved to maintain the diversity of population. The hybrid algorithm is applied to phase-only beam shaping to achieve main lobe broadening and side lobe depression. Simulation results demonstrate the superiority of the hybrid IWO and CS algorithm.

Modified chemical reaction optimization and its application in engineering problems.

Chemical Reaction Optimization (CRO) is a simple and efficient evolutionary optimization algorithm by simulating chemical reactions. As far as the current research is concerned, the algorithm has been successfully used for solving a number of real-world optimization tasks. In our paper, a new real encoded chemical reaction optimization algorithm is proposed to boost the efficiency of the optimization operations in standard chemical reactions optimization algorithm. Inspired by the evolutionary operation of the differential evolution algorithm, an improved search operation mechanism is proposed based on the underlying operation. It is modeled to further explore the search space of the algorithm under the best individuals. Afterwards, to control the perturbation frequency of the search strategy, the modification rate is increased to balance between the exploration ability and mining ability of the algorithm. Meanwhile, we also propose a new population initialization method that incorporates several models to produce high-quality initialized populations. To validate the effectiveness of the algorithm, nine unconstrained optimization algorithms are used as benchmark functions. As observed from the experimental results, it is evident that the proposed algorithm is significantly better than the standard chemical reaction algorithm and other evolutionary optimization algorithms. Then, we also apply the proposed model to address the synthesis problem of two antenna array synthesis. The results also reveal that the proposed algorithm is superior to other approaches from different perspectives.

Optimized VAA Based Synthesis of Elliptical Cylindrical Antenna Array for SLL Reduction and Beam Thinning Using Minimum Number of Elements

In this paper, new virtual antenna array (VAA) based synthesis techniques are introduced for side lobe level (SLL) reduction, beam thinning, and number of elements minimization for elliptical cylindrical antenna arrays (ECAA) of radar systems. Thereby, significant improvements in the array gain and directivity are achieved, which enhance the detection range and angular resolution of the radar. Furthermore, the overall implementation cost of the system is highly reduced by saving the number of elements and the corresponding RF chains and simplifying the feeding network. Firstly, the proposed technique decomposes the single transmit/receive ECAA into a separate transmit linear antenna array (LAA) and receive elliptical antenna array (EAA). Secondly, the number of antenna elements, element spacing, and excitations of the created LAA and EAA are optimized using particle swarm optimization (PSO) to produce efficient beamformed patterns. Finally, the Kronker product of the optimized LAA and EAA patterns is performed to form the optimized virtual ECAA (V-ECAA) pattern. We also introduced both the uniform feeding based V-ECAA technique and the non-uniform feeding based V-ECAA synthesis technique for more flexibility and better productivity in antenna arrays design. The simulation results revealed that the uniform feeding based V-ECAA provides an identical pattern to that of the traditional uniform feeding ECAA while saves the number of elements by 66.6%. While in the case of non-uniform feeding based V-ECAA, it provides much lower SLL and narrower HPBW than those of the ECAA while saving the number of elements by 63.8%. Furthermore, the HB is applied to provide additional beam thinning and SLL reduction of the proposed non-uniform V-ECAA that is denoted as (HBV-ECAA). The possibility of practical validations of the synthesized V-ECAAs is verified using the computer simulation technology (CST) microwave studio package, which gives users an integrated design environment and achieves realizable and robust designs.

Pattern Synthesis of Uniform and Sparse Linear Antenna Array Using Mayfly Algorithm

Pattern synthesis is a significant research focus in smart antennas due to its extensive use in several radar and communication systems. To improve the optimization performance of pattern synthesis of uniform and sparse linear antenna array, this paper presents an optimization method for solving the antenna array synthesis problem using the Mayfly Algorithm (MA). MA is a new heuristic algorithm inspired by the flight behavior as well as the mating process of mayflies, it has a unique velocity update system with great convergence. In this work, the MA was applied to linear antenna arrays (LAA) for optimal pattern synthesis in the following ways: by optimizing the antenna current amplitudes while maintaining uniform spacing and by optimizing the antenna positions while assuming a uniform excitation. Constraints of inter-element spacing and aperture length are imposed in the synthesis of sparse LAA. Sidelobe level (SLL) suppression with the placement of nulls in the specified directions is also implemented. The results gotten from this novel algorithm are validated by benchmarking with results obtained using other intelligent algorithms. In the synthesis of uniform 20-element LAA with nulls, MA achieved an SLL of -31.27 dB and the deepest null of -101.60 dB. Also, for sparse 20-element LAA, an SLL of -18.85 dB was attained alongside the deepest null of -87.37 dB. MA obtained an SLL of -35.73 dB and -23.68 dB for the synthesis of uniform and sparse 32-element LAA respectively. Finally, electromagnetism simulations are conducted using ANSYS Electromagnetics (HFSS) software, to evaluate the performance of MA for the beam pattern optimizations, taking into consideration the mutual coupling effects. The results prove that optimization of LAA using MA provides considerable enhancements in peak SLL suppression, null control, and convergence rate with respect to the uniform array and the synthesis obtained from other existing optimization techniques.

Method of synthesis of a digital antenna array with logic signal processing

Method of synthesis of a digital antenna array with logic signal processing

Nonequidistant antenna arrays synthesis based on genetic algorithm

A new approach to the synthesis of nonequidistant antenna arrays with uniform distribution based on the Genetic Algorithm of the global extrema search is introduced and analyzed. The technique is demonstrated for various uniform antenna array structure. The radiation pattern of the nonequidistant antenna array is formed using the Genetic Algorithm to reduce a side lobe level. A mathematical formula is presented to highlight the operation of objective function minimization.