PLANAR ARRAY SYNTHESIS WITH SIDELOBE REDUCTION AND NULL CONTROL USING INVASIVE WEED OPTIMIZATION

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.

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.

Pattern synthesis of non-uniform elliptical antenna arrays is presented in this paper. Only the element positions of the antenna arrays are optimized by the combination of differential evolution (DE) and invasive weed optimization (IWO) to reduce the peak side lobe level (PSLL) of the radiation pattern. In order to avoid the overlap of the array elements, the minimum spacing of the adjacent elements is constrained. Also, the beam width of the radiation pattern can be constrained effectively. Three elliptical antenna arrays that have 8, 12, and 20 elements are investigated. The synthesis results show that the introduced method can present a good side lobe reduction for the radiation pattern. Compared with other optimization methods, the method proposed in this paper can obtain better performance.

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.

A novel optimization method for multiple beamforming with null steering is proposed. Firstly, an invasive weed optimization method is improved in order to optimize the search depth. In the process of the seed diffusion, the crossover operation of genetic algorithm is introduced to modify the seed individuals, which can meliorate the searching ability and convergence speed of the algorithm. Then, the harmonic beamforming technology based on time modulated antenna array is presented, and multiple objectives about peak power and null steering are built. Finally, the improved invasive weed optimization algorithm is used in null forming based on pattern synthesis of antenna array, and the element excitation amplitude of time modulated antenna array is set to the excitation value obtained by the improved optimization algorithm. The simulation results show that the improved invasive weed optimization algorithm is superior to the conventional algorithm in performance. The simulation results show that forming null in the specified direction can be achieved while generating multiple beams.

Radiation pattern synthesis of a planar antenna array using relative elements axial rotation is proposed to generate broadside flattop or cosecant beams for surveillance, radars, and mobile communications. For a proof of concept, 5 x 5 planar Hertzian dipoles are utilized to synthesize all space-desired radiation patterns over a solid angle ratio of 13.4%. The rotation of each element is adjusted using a built-in MATLAB-based particle swarm optimization (PSO) technique. The deployed algorithm can be extended to include more elements and deploy different radiating elements.

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.

This communication presents for the first time a 16-element planar X-band bidirectional antenna array for beamforming applications. The planar (2D) antenna array is comprised of planar polygon slot antenna elements that utilize a metamaterial inspired reactive coupling element. Simulation and measurement results are presented for both a single antenna element and a 16-element planar array, which resides on a Liquid Crystal Polymer (LCP) substrate. Successful comparison between measured and simulated results verifies that the single antenna element achieves a 10 dB return loss bandwidth of 17.5% and the planar antenna array achieves a 10 dB return loss bandwidth of 25% both at a center frequency of approximately 11 GHz. The measured gain of the planar antenna array is more than 14.5 dBi with an efficiency of 65%. The overall size of the planar antenna array is 3.3λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sub> × 3.6λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sub> × 0.0093λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sub> at 11 GHz.

An ecologically inspired optimization algorithm, called invasive weed optimization (IWO), is presented for the design of non-uniform, planar, and circular antenna arrays that can achieve minimum side lobe levels for a specific first null beamwidth while avoiding the mutual coupling effects simultaneously. IWO recently emerged as a derivative-free real parameter optimizer that mimics the ecological behavior of colonizing weeds. For the present application, classical IWO has been modified by introducing a more explorative routine of changing the standard deviation of the seed population (equivalent to mutation step-size in evolutionary algorithms) of the algorithm. Simulation results over three significant instances of the circular array design problem have been presented to illustrate the effectiveness of the modified IWO algorithm. The design results obtained with modified IWO have been shown to comfortably beat those obtained with other state-of-the-art metaheuristics like genetic algorithm (GA), particle swarm optimization (PSO), original IWO and differential evolution (DE) in a statistically meaningful way.

Synthesizing antenna arrays is one of the most influential optimization problems in the electromagnetics community. In this paper, an improved fruit-fly optimization algorithm (FOA) [entitled averager engine linear generation mechanism of candidate solution of FOA (AE-LGMS-FOA)] is proposed to be used in antenna array synthesis. This improvement includes adding a new search mechanism to enhance the efficiency of algorithm during high-dimensional problems. After investigating its performance through a variety of benchmark functions, the proposed method is applied to several linear and planar array problems in terms of sidelobe reduction, null control, and thinning. During the problems, some properties of the algorithm are analyzed and the associated results are compared with other state-of-the-art methods and popular algorithms. Furthermore, various boundary conditions are reformulated for the algorithm and examined during the planar array synthesis. Finally, the AE-LGMS-FOA is utilized in synthesizing a U-slot microstrip array antenna with ultrawideband characteristics to verify its versatility and robustness in real-world array antenna problems. The optimized structure has an impedance bandwidth of 3.38 GHz, which indicates 181.6% improvement over the original structure’s bandwidth.

In this paper, a novel method for pattern synthesis of antenna arrays based on dynamic cooperative gray wolf optimizer algorithm is proposed. By introducing the dynamic cooperative weight factor, positions of the three leader wolves are weighted, and then the positions of next generation are updated. The improved algorithm emphasizes the leading role of the leader wolf, but also does not neglect the cooperation between the leadership wolves. Global optimal and local optimal can be well balanced and converge to the optimal solution quickly and effectively. The proposed algorithm has been successfully used to reduce the sidelobe level and form deep null steerings at designated directions which meets the design requirements.

An antenna pattern synthesis technique is presented which permits the design of planar antenna arrays when the array excitation is restricted to have an in-phase amplitude distribution. This technique is applicable to planar arrays of a wide variety of grid structures and can produce a sum pattern with controlled side lobe levels. It is also applicable to difference patterns (if the two halves of the array are excited out of phase). The approach involves minimizing a scalar-valued performance measure, called the cost function, via use of the conjugate gradient method. The unknowns in the cost function are the relative amplitudes of the elements of the array, which are kept positive by being set equal to the squares of real variables. Iteration starts with a uniform amplitude distribution; convergence to the desired pattern is stable and fast.

In this paper, a new modified method is presented for the synthesis of a linear antenna array to obtain a desired array pattern (shaped or pencil) with low side lobe level. Based on the original invasive weeds optimization (IWO), our modified IWO (MIWO) uses the process of mutation for the calculation of standard deviation. The shaped beam pattern is synthesized by respecting a desired cosecant pattern and supressing side lobe level to -25 dB. To achieve the desired pattern, both amplitude and phase of each element in the array are optimized when the spacing between the elements is fixed to the half wavelength. For the desired pencil beam pattern, the inter-element spacing’s are controlled while maintaining uniform excitations. Selected examples, for both shaped and pencil beam, are presented to show the effectiveness and flexibility of the proposed method. DOI: http://dx.doi.org/10.5755/j01.eee.21.5.13332

본 논문에서는 2차 함수 곡선의 회전체 곡면 위에 있는 배열 안테나의 빔 합성을 위한 Enhanced Adaptive Genetic Algorithm(EAGA)을 제안하였다. 제안된 알고리즘은 더 빠른 수렴 속도와 더 낮은 비용함수 값을 얻기 위해 Adaptive Genetic Algorithm(AGA)과 Invasive Weed Optimization(IWO)을 결합시켰다. 각 안테나 소자의 급전 크기와 위상의 최적화된 값은 EAGA를 통해 구하였으며, 이 결과를 통해 EAGA가 컨포멀 배열 안테나의 패턴 합성 알고리즘으로써 AGA보다 더 우수함을 보였다. This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

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.