Improved Fruit-Fly Optimization Algorithm and Its Applications in Antenna Arrays Synthesis

Far-field pattern synthesis of small antenna arrays is a nontrivial problem. Typically radiation patterns are required to exhibit low sidelobe levels, whilst maintaining the ability to scan the main beam in space. Mutual coupling is a pertinent problem when the number of antenna elements is small, often precluding the use of conventional tapering algorithms. In this paper a technique previously employed to compensate for mutual coupling in linear arrays is extended to include small planar antenna arrays. The method consists of the calculation of the coupling coefficients between the array elements, which are then formed into a matrix and used to compensate for the effects of mutual coupling. It is then shown that this method is not suitable for all planar array configurations and a new technique is developed which allows the calculation of coupling matrices for these element configurations. Measured data from a small planar antenna array is presented, with the outlined methods employed to produce low sidelobe sum and difference beams.

Pattern Search optimization with applications on synthesis of linear antenna arrays

This paper introduces an application of the dandelion optimization (DO) algorithm in antenna arrays. This is the first time that the DO algorithm has been used for optimizing antenna arrays. For antenna array optimization, sidelobe level (SLL) and deep nulls are key technical indicators. A lower SLL can improve the signal-to-noise ratio and reduce the impact of clutter signals outside the main beam. Deep nulls need to be aligned with the direction of interference to eliminate the influence of interference sources. The combination of the two can effectively improve the anti-interference ability of the entire system. Therefore, antenna arrays with ultra-low sidelobes and ultra-deep nulls are currently hot in the field of antenna array design and are also some of the key technologies needed to achieve modern high-performance radar systems. As a new type of evolutionary algorithm inspired by nature, the DO algorithm is inspired by the wind propagation behavior of dandelions in nature. This algorithm iteratively updates the population from three stages of ascent, descent, and landing, ultimately finding the optimal position. It has good optimization ability in solving complex problems such as those involving nonlinearity, discreteness, and non-convexity, and the antenna array pattern synthesis optimization problem belongs to multivariate nonlinear problems. Therefore, the DO algorithm can be effectively applied in the field of antenna array optimization. In this work, we use the following method to obtain an optimized pattern of a linear array with the lowest sidelobe level (SLL), null placement in particular directions, and a lower notch in particular directions: by controlling the antenna array’s element spacing and leaving the phase unchanged to optimize the current amplitudes and by controlling the excitation current and phase fixation of the antenna array and changing the element spacing. In the first and second examples, different algorithms are used to reduce the SLL of the antenna. In the first example, the DO algorithm reduces the SLL to −33.37 dB, which is 2.67 dB, 2.67 dB, 3.77 dB, 2.74 dB, and 2.52 dB lower than five other algorithms. In the second example, the SLL optimized by the DO algorithm is −42.56 dB, which is 5.04 dB and 1.48 dB lower than two other algorithms. In both examples, the DO algorithm reduces the SLL lower than other algorithms when the main lobe of the antenna is not significantly widened. Examples 3, 4, and 5 use the DO algorithm to optimize the amplitude of the current, generating deep nulls and deep notches in specific directions. In Example 3, the DO algorithm obtains a depth of nulls equal to −187.6 dB, which is 66.7 dB and 44.3 dB lower than that of the flower pollination algorithm (FPA) and the chaotic colony predation algorithm (CCPA), respectively. In Example 4, the deep null obtained by the DO algorithm is as low as −98.69 dB, which is 6.67 dB lower than the deep null obtained by the grey wolf optimization (GWO) algorithm. In Example 5, the deep notch obtained by the DO algorithm is as low as −63.1 dB, which is 6.4 dB and 1.9 dB lower than the spider monkey optimization (SMO) algorithm and the grasshopper optimization algorithm (GOA), respectively. The data prove that the DO algorithm produces deeper nulls and notches than other algorithms. The last two examples involve reducing sidelobe levels and generating deep nulls by optimizing the spacing between elements. In Example 5, the SLL obtained using the DO algorithm is −22.8766 dB, which is 0.1998 dB lower than the lowest SLL of −22.6768 dB among other algorithms. In Example 6, the SLL obtained using the DO algorithm is −20.1012 dB, and the null depth is −125.1 dB, which is 1.592 dB lower than the SLL obtained by the cat swarm optimization (CSO) algorithm and 19.1 dB lower than the deep null obtained by the GWO algorithm, respectively. In summary, the results of six simulation experiments indicate that the DO algorithm has better optimization ability in linear array optimization than other evolutionary algorithms.

Planar antenna array design is one of the most important electromagnetic optimization problems of current interest. This paper introduces a recently developed metaheuristic algorithm, known as the Invasive Weed Optimization (IWO), to the pattern synthesis of planar antenna arrays with desired pattern nulls and sidelobe level by amplitude-only and position-only optimization. The steps in the problem formulation are presented along with a design example that illustrates the performance of the IWO algorithm. Three examples have been presented and solved. Simulation results are proposed to compare with published ones to verify the efiectiveness of the IWO algorithm for planar arrays.

The pattern synthesis technique of antenna arrays has a wide range of applications in radar and communication systems, which is an important research direction in the field of smart antennas. In order to improve the optimization performance of pattern synthesis of linear antenna arrays, an optimization method based on the Modified RIME Optimization Algorithm (MRIME) is proposed. RIME is a new heuristic algorithm inspired by the condensation process of frost ice in nature, which has a unique update mechanism with strong convergence as well as randomization. In the present work, MRIME is used for optimal pattern synthesis of a linear antenna array (LAA). One part of the present study is to optimize the side lobe level by optimizing the antenna current amplitude while maintaining a uniform spacing; the other part is to optimize the antenna position while assuming a uniform excitation in the synthesis of a sparse LAA, where constraints are imposed on the spacing of the array elements and aperture length, and suppression of the side lobe level with the position of the zeros in the specified direction is also achieved. In this article, simulation experiments for uniform linear arrays as well as sparse linear arrays are presented in detail, and the results show that the MRIME optimization algorithm outperforms most of the existing evolutionary classes of optimization algorithms in optimizing the side lobe level. This illustrates the potential of utilizing the MRIME optimization algorithm for antenna arrays and various other electromagnetism-related challenges.

A method of the amplitude–phase multicriteria synthesis of a Pareto-optimal antenna array is proposed. The method is based on representation of the initial antenna array synthesis problem in the form of successively solved partial problems (subproblems) with small dimensionality. Each subproblem is reduced to determination of Pareto-optimal parameters of the amplitude–phase distribution of an additional beam added to the initial radiation pattern.

The synthesis of a nonuniform antenna array with as few elements as possible has considerable practical applications. This paper introduces a new non-iterative method for linear array synthesis based on the matrix pencil method (MPM). The method can synthesize a nonuniform linear array with a reduced number of elements, and can be also used to reduce the number of elements for linear arrays designed by other synthesis techniques. In the proposed method, the desired radiation pattern is first sampled to form a discrete pattern data set. Then we organize the discrete data set in a form of Hankel matrix and perform the singular value decomposition (SVD) of the matrix. By discarding the non-principal singular values, we obtain an optimal lower-rank approximation of the Hankel matrix. The lower-rank matrix actually corresponds to fewer antenna elements. The matrix pencil method is then utilized to reconstruct the excitation and location distributions from the approximated matrix. Numerical examples show the effectiveness and advantages of the proposed synthesis method.

Most of the recent state of the art circular antenna arrays (CAA) synthesis techniques attempted to synthesize the Chebyshev linear array patterns in the azimuth plane. In this paper, a new Genetic algorithm optimization-based technique for Uniform CAAs synthesis to realize a desired Chebyshev pattern in the elevation plane is introduced. The proposed technique maintains the same number of antenna elements as the linear antenna array. While the CAA diameter, elements angular distribution, and elements excitations are optimized to synthesize the desired pattern. The CAA diameter is optimized around the array size of the linear antenna array. And the angular positions of the antenna elements are non-uniformly distributed on the circle circumference using the GA optimization. While a closed-form expression for the corresponding elements excitations is derived to determine these excitations using a deterministic equation solving technique. Several simulations are performed to verify the effectiveness of the proposed technique.

In the theory of synthesis of MIMO antenna arrays for mm-Wave and THz applications, methods based on some a priori assumptions either about the amplitude-phase distribution over the length of the array are often used. Also the spatial location with the subsequent solution of the optimization problem is a common task in the conformal antennas design. In this paper, we analyze the possibilities of synthesizing a non-uniformly spaced array equivalent to a uniform one with a given amplitude-phase distribution. We synthesized the arrangement of elementary emitters with a known radiation pattern for the optimal antenna array by the criterion of sidelobe level suspension using two modifications of the particle swarm method and a genetic algorithm. This is implemented using evolutionary programming-real valued genetic algorithm (GA) and particle swarm optimization algorithm (PSO) under some constraints, minimizing the maximum side-lobe level of the planar array. It is shown that the proposed method can significantly reduce the pattern distortion as well as the side-lobe level. The obtained numerical results are compared with each other. The Best-Weights for 18 elements array are listed. The radiation patterns are presented for different number of elements.

A mean variance mapping optimization algorithm for three types of antenna array synthesis examples is presented. Mean variance mapping optimization is based on the strategic transformation used for mutating the offspring built on mean variance of a certain dynamic population. The first set of examples is based on side-lobe suppression and null control by controlling element positions with mean variance mapping optimization under constraints to beam width. In the second group of examples, mean variance mapping optimization becomes an optimization tool to calculate the amplitude and phase values of antenna array elements to synthesize shaped beams. In the last set of examples, mean variance mapping optimization is used to mitigate the effect of failure elements on the pattern by recalculating the amplitude values of remaining elements. Additionally, a modification that provides a good balance between exploitation and exploration is applied to the mean variance mapping optimization algorithm to improve its stability and accuracy. The simulation results showed that the proposed mean variance mapping optimization is an effective and easy implementable technique for different antenna array synthesis problems.

This monograph presents innovative methods for constructing two-dimensional non-equidistant antenna arrays (AAs), particularly designed for radio telescopes operating in the 8–80 MHz range. The work introduces direct and straightforward techniques, emphasizing configurations based on Latin squares and their triangular matrices. These methods ensure full spatial frequency coverage with high rarefaction and minimal lateral radiation. Key contributions include the first use of a Latin square matrix in AA construction, the pioneering combination of circular difference sets and Latin square matrices for planar sparse arrays, and the integration of Latin square and lower triangular matrices in planar sparse array design. The proposed matrix method is more efficient and direct compared to traditional iterative and deletion-based optimization approaches. This book is intended for scientists and specialists involved in developing remote sensing methods and technologies using radiation from existing ground and space radio engineering systems. It is also valuable for students and educators in radiophysics, offering a comprehensive approach to AA design that could advance both academic study and practical applications in radio astronomy.

Beam synthesis remains one of the most difficult problems for an antenna array designer, this task being made more difficult when one limits the number of elements to a handful. Pattern synthesis in planar arrays is often achieved by the sampling of a continuous aperture distribution at the element locations. In the case of arrays of limited numbers of elements this produces errors that can unacceptably distort the radiation pattern. When one also then considers the effects of mutual coupling between the antenna elements, the application of ideal element weights derived in this way are no longer valid. In the paper a technique is presented, using the concept of retrodirective beams, that can achieve a low sidelobe beam from a continuous distribution on a circular aperture. The theory is then extended to include a planar array of antenna elements. This is achieved by the addition of retrodirective beams to the uniform beam pattern of the array. Measured data is presented for a small planar array antenna using the derived method. A method for correction of the element weights, to minimise the effects of mutual coupling, producing low sidelobe radiation patterns is then applied. No knowledge of the antenna array's coupling coefficients are required.

The work carried out the calculation and synthesis of antenna arrays used in radio-electronic complexes on unmanned aerial vehicles. The analytical model is designed to find asymptotic estimates of the polarization components of the electric field of the grating in the far zone of the carrier surface; the results obtained with its use are the initial data for constructing a technique for the numerical solution of a boundary value problem for a grating on a carrier surface in the CST MWS electrodynamic simulation environment. The synthesis of gratings with the maximum achievable coefficient of directional action is carried out with the control of radiation patterns at a given set of angles. A two-mirror antenna system has been calculated. It is shown that with an increase in the number of re-reflections taken into account, the convergence of the result for the calculated characteristics of the antenna is observed. To test the proposed method, the same antenna was calculated using the integral equation method. The comparison showed a high degree of agreement between the results obtained by two different methods. The results of the simulation based on a software algorithm designed to quantify the input matching at the input of a multichannel frequency-scanning antenna array power divider are presented. It was found that when performing wide-angle scanning in a relative frequency band of more than a few percent, the disadvantage of the known method for eliminating the normal effect is a sharp deterioration in matching in the lower and upper frequencies of the operating range. A new method is proposed based on an automated iterative process of optimizing the divider geometry, which makes it possible to obtain an acceptable match over the entire operating frequency band. The feasibility of switching from a serial power divider construction scheme to a series-parallel scheme is analyzed for wide-angle scanning in a relative frequency band of about 5%.

The aim of this paper is two-fold. First, the trade-off between directivity, beam-width, side-lobe-level, number of radiating elements, and scanning range of planar antenna arrays is reviewed, and some simple ready-to-use formulas for the preliminary dimensioning of equispaced planar arrays are provided. Furthermore, the synthesis of sparse planar arrays, and the issue of their reduction in directivity, is analyzed. Second, a simple, yet effective, novel approach to overcome the directivity issue is proposed. The presented method is validated by several synthesized layouts; the examples show that it is possible to synthesize sparse arrays, able to challenge with equispaced lattices in terms of directivity, with a significant reduction of the number of radiators.

Far-field pattern synthesis of small antenna arrays is a nontrivial problem, mainly due to mutual coupling, often precluding the use of conventional tapering algorithms. A technique to compensate for mutual coupling in small linear antenna arrays is described. The method consist of calculations of a coupling matrix, which is then used to compensate for the effects of mutual coupling. Two different methods of the calculation of coupling coefficients between the array elements are presented. In order to validate the methods, measured data for a small linear antenna array is presented and discussed.