Aperiodic Linear Arrays Research Articles

Optimal Amplitude–Density Synthesis of Linear Aperiodic Arrays

New deterministic procedures for the design of linear aperiodic arrays are described which permit exploiting, in a combined way, both the positions and the excitation amplitudes of the array elements obtaining a pattern which optimally fits, in terms of a weighted L2 norm, the pattern of a reference linear continuous aperture. A first numerical procedure is based on alternating optimization of positions and amplitudes by means of closed-form convex projectors. Sufficient conditions for the solution to be optimal are established. A second numerical procedure is based on a domino-like sequential determination of the unknowns which can be iterated to convergence. Additionally, analytical asymptotic expressions for the optimal inter-element spacing and amplitude are derived by means of variational techniques. The optimal asymptotic inter-element spacing is demonstrated to be proportional to the reference tapering to the power (-2/3) while the optimal asymptotic array amplitude is proportional to the reference tapering to the power (1/3). For aperiodic arrays with equiamplitude excitation it is proved that the optimal inter-element spacing is proportional to the reference tapering to the power (-1). Based on these asymptotic dependencies, closed-form analytical solutions are obtained for amplitudes and positions of the elements. Several numerical results confirm the effectiveness and accuracy of the new procedures.

Randomly overlap subarray feeding network to reduce number of phase shifter in 28GHz.

Synthesizing antenna arrays for fifth-generation communication technology is the most significant issue in the electromagnetic industry and academia. This paper focused on a comprehensive algorithm for developing a 5G base station antenna array. The suggested algorithm aims to provide a high-gain array antenna with a continuous wide scan angle without a grating lobe, as much as a compact size, low cost, and simplicity of fabrication, especially in the array feeding network system. The best architecture is specified by comparing the array factor of numerous subarray combinations to achieve the grating lobe's minimum level. By considering additional limitations in our approach, such as different subarray symmetric architecture, complex weighting function, minimal number of overlapped elements, and an optimal number of microstrip layers, we improve the specification over previous research and lower the runtime procedure. The proposed method is also used to construct a linear array antenna with 49 radiating elements for a 5G base station antenna operating at 28 GHz. Consequently, the number of phase shifters has been reduced by more than 53%, significantly improving over earlier efforts. Then a hybrid genetic algorithm and a particle swarm optimization technique are applied to determine the optimal values of excitation coefficients to control side lobe level(SLL) and beam scanning. The amplitude and phase step variations are calculated as 0.1 and 1°, respectively. HPBW of 2.8°, gain of 28 dB, scanning up to ± 25° in one direction, and SLL below -24 dB are the electromagnetic properties of the designed aperiodic linear array. An example of implementing the suggested method, a 16-element array with a random overlap subarray structure, including the feeding network and microstrip antenna element, will be modeled using a full-wave simulator. The simulation results show that the proposed algorithm is efficient for designing array topology.

Design of Beam-Steerable Aperiodic Linear Array Antenna With Improved Peak SLL Using Strip-Projection Method

This article discusses the design of the beam-steerable aperiodic linear array antenna with improved sidelobe level (SLL), using the strip-projection method. The strip projection method uses the area of rotated higher-dimensional lattice and projects it to lower dimensions to generate an aperiodic array. This article describes the modeling and analysis of such an array and its optimization for the desired far-field performance. The aperiodic arrays are also generated using various evolutionary optimization algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and Jaya algorithms. The far-field performance of the generated aperiodic arrays is compared with the conventional periodic array. The proposed 21-element aperiodic array is also populated with a X-band electromagnetically coupled patch antenna and phase shifter designed using varying width of the high dielectric material. The aperiodic patch array antenna is also developed and characterized for various beam scan angles. A significant improvement of 5.72 dB in peak SLL is achieved at ±30° beam scan angle.

Gaussian approach for the synthesis of phase-only beam-scanning linear aperiodic antenna arrays

This paper describes a method for the synthesis of linear aperiodic antenna arrays with beam scanning capability. The algorithm is based on a recently proposed Gaussian approach, regarding linear aperiodic arrays of isotropic elements with uniform amplitude distribution, which yields the optimal element positions of the array in such a way as to form a Gaussian beam of prescribed properties. The latter approach is here extended to solve a problem of beam scanning in an angular region of interest. Precisely, the array element positions are determined in such a way as to form a pencil beam, that can be pointed in any direction of the angular region of interest by a suitable distribution of the excitation phases. Thus, a continuous beam scanning can be performed by phase-only control. It is also shown that the alternating projection approach can mitigate the pattern degradation that arises for pointing angles near the end-fire direction.

Low-Complexity Phase-Only Scanning by Aperiodic Antenna Arrays

This letter proposes a simple and fast method for phase-only beam-scanning of linear aperiodic arrays. The method adopts a three-step procedure, consisting in the placement of the array elements by proper distribution functions, in the synthesis of the excitation amplitudes by an extended Gaussian approach, and in the evaluation of the excitation phases by a closed-form shifting. Numerical examples and comparisons with existing approaches are presented to check the effectiveness of the method, with the final aim of confirming its satisfactory behavior in terms of tradeoff between accuracy and computational cost.

Reducing the Sidelobe Power Pattern of Linear Broadside Arrays by Refining the Element Positions

In this letter, a simple and fast method is presented for improving the linear array radiation patterns produced by the existing synthesis algorithms. Given a linear aperiodic array with elements lying at specified positions, having uniform distribution of the excitations and radiating a pencil beam in the broadside direction, the proposed approach iteratively modifies the positions of the elements in order to reduce the power radiated in the sidelobe region. Numerical examples show the effectiveness of the method, and the effects of the sidelobe power reduction on other parameters of the antenna are examined.

Synthesis of Broadside Linear Aperiodic Arrays With Sidelobe Suppression and Null Steering Using Whale Optimization Algorithm

In this letter, a new optimization algorithm named whale optimization algorithm (WOA) is introduced and applied to the synthesis of uniformly excited broadside linear aperiodic arrays with sidelobe suppression and null steering under constraints on beamwidth requirements. Three design examples of pattern synthesis have been chosen to illustrate the effectiveness and superiority of WOA when compared to synthesis techniques described in the literature. The results show that the WOA achieves lowest maximum sidelobe level combined with deepest null depth level with narrow first null beamwidth relative to other state-of-the-art algorithms. The WOA results and convergence tests demonstrate superior applicability of this novel optimization algorithm.

Multi-Objective Evolutionary Optimization of Aperiodic Symmetrical Linear Arrays

In this paper, a multi-objective approach is applied to the design of aperiodic linear arrays of antennas. The adopted procedure is based on a standard Matlab implementation of the Controlled Elitist Non-Dominated Sorting Genetic Algorithm II. Broadside symmetrical arrays of isotropic radiators are considered with both uniform and non-uniform excitations. The work focuses on whether, and in which design conditions, the aperiodic solutions obtained by the adopted standard multi-objective evolutionary procedure can approximate or outperform the Pareto-optimal front for the uniformspacing case computable by the Dolph-Chebyshev method.

Synthesis of linear aperiodic array using Cauchy mutated cat swarm optimization

A novel Cauchy mutated cat swarm optimization (CMCSO) that features effective global search capabilities with fast convergence is introduced in this paper. The Cauchy mutation enables the cats of the cat swarm optimization (CSO) algorithm to seek their positions in directions that avoid the problem of premature convergence and local optima. In this communication, CMCSO is applied to the synthesis of linear aperiodic arrays for minimizing sidelobe level and controlling the null positions. Various synthesis examples are considered and the obtained results are compared with linear aperiodic array designs from literature. Numerical results demonstrate that the proposed method is superior to existing methods in terms of accuracy and convergence speed. Some of the synthesized aperiodic array designs are implemented with wire dipole antenna elements using a full-wave electromagnetic simulator. Furthermore, experiments are conducted on several standard benchmark complex multimodal problems to demonstrate the effectiveness of the proposed method. The sensitivity analysis is performed on different parameters of CMCSO to demonstrate their influence on the overall performance of the benchmark and antenna array synthesis problems.

Linear Aperiodic Array Synthesis Using Differential Evolution Algorithm

In this letter, a modified differential evolution (DE) based on harmony search algorithm is developed for the linear aperiodic array synthesis. By adding the parameter selection strategy into the classic differential evolution, the modified DE combines the good local search capability of the classic DE and the great search diversity of harmony search algorithm. The pattern optimization simulations of the linear aperiodic array verify that it converges faster and requires less computation.

Linear Aperiodic Array Synthesis Using an Improved Genetic Algorithm

A novel algorithm on beam pattern synthesis for linear aperiodic arrays with arbitrary geometrical configuration is presented in this paper. Linear aperiodic arrays are attractive for their advantages on higher spatial resolution and lower sidelobe. However, the advantages are attained at the cost of solving a complex non-linear optimization problem. In this paper, we explain the Improved Genetic Algorithm (IGA) that simultaneously adjusts the weight coefficients and inter-sensor spacings of a linear aperiodic array in more details and extend the investigations to include the effects of mutual coupling and the sensitivity of the Peak Sidelobe Level (PSL) to steering angles. Numerical results show that the PSL of the synthesized beam pattern has been successfully lowered with the IGA when compared with other techniques published in the literature. In addition, the computational cost of our algorithm can be as low as 10% of that of a recently reported genetic algorithm based synthesis method. The excellent performance of IGA makes it a promising optimization algorithm where expensive cost functions are involved.

Synthesis of linear aperiodic arrays using a self-adaptive hybrid differential evolution algorithm

A self-adaptive hybrid differential evolution algorithm is proposed to optimise linear aperiodic arrays with a minimum peak sidelobe level. The proposed method incorporates a local search operation into a differential evolution (DE) algorithm to accelerate its convergence rate. Moreover, the self-adaptive parameter control approach is employed to avoid tuning the parameters of the DE algorithm. Synthesis examples are compared with the linear aperiodic array designs in the literature. Numerical results demonstrate that our approach is superior to existing algorithms in terms of the high-quality solutions and relatively small computational cost.

Design of wideband aperiodic linear arrays by constrained differential evolution algorithm

The element placement plays a crucial role in array performance. Especially, aperiodic placement technique is a very effective approach to remove grating lobes and minimize the sidelobe level (SLL) of an array. In this article, a wideband aperiodic array has been designed by a constrained differential evolution algorithm (DE). As a practical application, multiple optimization constraints, such as the given aperture length, the bandwidth, the number of elements and the minimum interelement spacing, are considered. Hence, minimizing SLL for the wideband aperiodic array can be formulated as a constrained optimization problem. Some synthesis examples are solved by the constrained DE. Numerical results demonstrate that the constrained DE is an effective approach for minimize SLL when all the constraint conditions are satisfied. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011. © 2011 Wiley Periodicals, Inc.

Grating Lobe Reduction in Aperiodic Linear Arrays of Physically Large Antennas

We present performance bounds obtained from the optimization of the sidelobe levels of aperiodic linear arrays. The antennas comprising these arrays are large compared to the distance between neighboring antennas, a case not addressed in previously published work. This optimization is performed in pattern-space and is applicable over a wide range of scan angles. We show that grating lobes can be suppressed even when the elemental antennas are several wavelengths in size, provided that the ratio of the antenna size to the average spacing between the antenna center-points does not exceed 80%.

Nature-Based Design of Aperiodic Linear Arrays with Broadband Elements Using a Combination of Rapid Neural-Network Estimation Techniques and Genetic Algorithms

The developments presented in this paper address the challenge of determining the optimal element positions in nonuniformly spaced broadband phased-array antennas in order to best meet desired performance criteria. Specifically, this is accomplished by introducing a new nature-based design technique that couples a robust genetic-algorithm (GA) optimizer with rapid neural-network (NN) estimation procedures. These provide performance criteria as functions of the element positions over the entire scanning range and bandwidth of operation. The objective of this GA-NN technique is to determine the optimal element positions for a broadband aperiodic linear phased-array antenna in order to minimize element VSWRs and sidelobe levels. The NN estimation procedures circumvent the need for computationally intensive full-wave numerical simulations during the optimization process, which would ordinarily render such an optimization task impractical. The effectiveness of the new GA-NN design synthesis technique is demonstrated by considering an example where a nonuniformly spaced linear phased array of ten stacked patch antennas is optimized for operation within a given bandwidth and scanning range.

The diffraction spectrum of a general family of linear quasiperiodic arrays

The author studies the diffraction spectrum and the structure factor of quasicrystalline, aperiodic, linear arrays with two arbitrary characteristic measure lengths, produced by a fairly general family of generating rules depending on two parameters. The calculation is performed by actually constructing the two-dimensional periodic structure whose projection will result in the desired linear aperiodic array. Distributions of some sequences of irrational numbers modulo 1 are derived as a byproduct of the main subject.

A new approach to array geometry for improved spatial spectrum estimation

In this letter, we address the problem of element placement in a linear aperiodic array for use in spatial spectrum estimation. By making use of a theorem by Caratheodory, it is shown that, for a given number of elements, there exists a distribution of element positions which, for uncorrelated sources, results in superior spatial spectrum estimators than are otherwise achievable. The improvement is obtained by constructing an augmented covariance matrix, made possible by the choice of element positions, with dimension greater than the number of array elements. The augmented matrix is then used in any of the known spectrum estimation methods in conjunction with a correspondingly augmented search pointing vector. Examples are given to show the superior detection capability, the larger dynamic range for spectral peak to background level, the lower sidelobes, and the relatively low bias values, when one of the known spectrum estimation techniques based on eigenstructure is used.