Antenna Array Synthesis Research Articles

MIMO radar antenna array synthesis with a hybrid approach based on GA and PSO

This study proposes a hybrid approach to synthesise the MIMO radar antenna arrays with low peak side lobe levels (PSLLs). In this approach, the positive features of genetic algorithm (GA) and particle swarm optimisation (PSO) have been integrated to find the optimal array arrangements. Also, in order to avoid prematurity in GA process, an improved adaptive operator is adopted for the adaptive adjustment of crossover probability and mutation probability. The simulation validation, carried out on the synthesised pattern of MIMO radar, shows that, the optimal PSLLs and convergence performance have been achieved by the hybrid approach compared to GA and PSO, respectively.

Subarrayed Antenna Array Synthesis Using Ternary Adjusting Method

Ternary adjusting method is proposed and combined with particle swarm optimization (PSO) algorithm for subarrayed antenna array synthesis. Ternary variables are introduced to represent element adjustments between adjacent subarrays. Compared to previous methods, rounding-off operations are not required any longer, and the equation constraint of the fixed total element number is also removed, which effectively reduces the complexity of implementation while obtaining improved topology exploration capability simultaneously.

Synthesis of Phase-Only Reconfigurable Linear Arrays Using Multiobjective Invasive Weed Optimization Based on Decomposition

Synthesis of phase-only reconfigurable array aims at finding a common amplitude distribution and different phase distributions for the array to form different patterns. In this paper, the synthesis problem is formulated as a multiobjective optimization problem and solved by a new proposed algorithm MOEA/D-IWO. First, novel strategies are introduced in invasive weed optimization (IWO) to make original IWO fit for solving multiobjective optimization problems; then, the modified IWO is integrated into the framework of the recently well proved competitive multiobjective optimization algorithm MOEA/D to form a new competitive MOEA/D-IWO algorithm. At last, two sets of experiments are carried out to illustrate the effectiveness of MOEA/D-IWO. In addition, MOEA/D-IWO is compared with MOEA/D-DE, a new version of MOEA/D. The comparing results show the superiority of MOEA/D-IWO and indicate its potential for solving the antenna array synthesis problems.

Bees algorithm for interference suppression of linear antenna arrays by controlling the positions of selected elements

An efficient method based on bees algorithm (BA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling only the positions of selected elements. The BA is an optimization algorithm inspired by the natural foraging behavior of honey bees to find the optimal solution. Simulation results for Chebyshev patterns with the imposed single and multiple nulls are given to show the effectiveness of the proposed method.

Linear Antenna Array Synthesis Using Orthogonal Artificial Bee Colony Algorithm

Linear Antenna Array Synthesis Using Orthogonal Artificial Bee Colony Algorithm

BEAM STEERING IN SMART ANTENNAS BY USING LOW COMPLEX ADAPTIVE ALGORITHMS

Array antenna systems are often used to enhance the received signal to interference and noise ratio wh en the signal operates in heavily jammed environment. Proper modeling of the received data at different antenna elements is impo rtant when evaluating the performance of this system, especially when both th e signal and interference have wide frequency bands .. The antenna output is the linear combination of data from all the antenna ele ments. In conventional narrowband beam forming, tim e sequences at different antenna elements are related by some fixed phase sh ift. The phase shift is determined by the wave form s direction of arrival (DOA). In this paper, an efficient method for the pattern synthesis of the linear antenna arrays with the pre scribed nulling and steering lobe is presented. The proposed method is based on Least Me an Square (LMS) algorithm provide a comprehensive atreatment of the signal model used for beam forming, as well as, describing adaptive algorithms to adjust the weigh ts of an array. In order to improve the convergence rate of LMS algorithm in sm art antenna system, in this paper we proposes a ne w normalized LMS (NLMS) algorithm, This new algorithm can be treated as a b lock based simplification of NLMS algorithm which gsatisfactory performance in certain applications in comparison w ith conventional NLMS recursion, i.e., BBNLMS algor ithm. By taking advantage of spatial filtering, the proposed scheme promises to reduce the bandwidth required for transmitting d ata by improving convergence rate. The performance of the BBNLMS algorithm in th e presence of Multi-path effects and multiple users is analyzed using MATLAB simulations. The simulations when compared to that of the LMS algorithm, the results suggest that BB NLMS algorithm can improve the convergence rate and lead to better system effi ciency.

Combination of fast Fourier transform and self-adaptive differential evolution algorithm for synthesis of phase-only reconfigurable rectangular array antenna

Reconfigurable antenna arrays are often capable of radiating multiple patterns by altering the excitation phases of the array elements. In this paper, an efficient method based on FFT is presented for generating dual-radiation pattern from a single rectangular planar array by modifying the excitation phases of the array elements while sharing common amplitudes. The common amplitudes shared by both the patterns and the phases which play the role of turning between the two patterns when updated over zero phase among the elements are computed using Self-adaptive Differential Evolution (SaDE) algorithm. Two different beam-pairs of pencil/pencil and pencil/flat-top are generated from the proposed array while maintaining precise design specifications. The proposed method greatly reduces the computational time as compared with the conventional method for calculating beam patterns. The dynamic range ratio of the excitation amplitudes are kept below a threshold level to reduce the design complexity of the attenuators at the feed network level and to minimize the effect of mutual coupling among the array elements. To illustrate the effectiveness of SaDE, the fitness functions associated with the two beam-pairs are minimized individually using differential evolution (DE) algorithm and particle swarm optimization (PSO) algorithm. Results clearly show the superiority of SaDE over DE and PSO to handle the proposed problem.

Hybrid MUSIC Dolph–Chebyshev algorithm for a smart antenna system

ABSTRACTThis paper presents practical design of a smart antenna system based on direction‐of‐arrival estimation and Dolph–Chebyshev beam forming. Direction‐of‐arrival estimation is based on the multiple signal classification algorithm for identifying the directions of the source signals incident on the sensor array comprising the smart antenna system. The smart antenna system design involves a hardware part, which provides real data measurements of the incident signals received by the sensor array. This paper presents the Dolph–Chebyshev method for the synthesis and design of antenna arrays with periodic element spacing. A Field‐Programmable Gate Array implementation is presented for an antenna array application employing digital beamforming. The array comprises 10 elements, equal in number receiving radio frequency and intermediate frequency components, as well as a Spartan‐3E Field‐Programmable Gate Array‐based unit, which is responsible for the control of the array. Low‐cost and switched‐beam, and fully adaptive antenna array suitable for 2‐GHz applications are proposed in this paper. Copyright © 2013 John Wiley & Sons, Ltd.

Planar Antenna Array Pattern Synthesis Using a Taguchi Optimization Method

The synthesis of planar antenna array has many practical applications. In this paper, we have used the Taguchi’s method to synthesize and optimize radiation patterns. Numerical examples of planar arrays were presented in order to show the high efficiency of accomplishing the desired radiation pattern with using only the synthesis on phase. The results were validated by planar array antenna patch (Rectangular patch with 64 elements) and simulated by software CST 2011 (CST microwave studio) at the frequency of 2.45 GHz.

Synthesis of antenna arrays with an efficient multiobjective differential evolution algorithm

An efficient multiobjective differential evolution algorithm for array synthesis is proposed in this article. By introducing novel strategies in the generalized differential evolution GDE3, the proposed algorithm can generate a better converged and distributed Pareto front than the standard GDE3. Five typical benchmark functions are optimized by the proposed improved GDE3 IGDE to verify its effectiveness. Furthermore, the proposed algorithm is applied in two-pattern synthesis problems, including an unequal spaced linear array and a conformal array. The superior performance of the proposed IGDE demonstrates that it is an efficient and competitive algorithm in the function optimization, pattern synthesis, and other electromagnetic problems. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:161-169, 2014.

The Wind Driven Optimization Technique and its Application in Electromagnetics

A new type of nature-inspired global optimization methodology based on atmospheric motion is introduced. The proposed Wind Driven Optimization (WDO) technique is a population based iterative heuristic global optimization algorithm for multi-dimensional and multi-modal problems with the potential to implement constraints on the search domain. At its core, a population of infinitesimally small air parcels navigates over an $N$ -dimensional search space following Newton's second law of motion, which is also used to describe the motion of air parcels within the earth's atmosphere. Compared to similar particle based algorithms, WDO employs additional terms in the velocity update equation (e.g., gravitation and Coriolis forces), providing robustness and extra degrees of freedom to fine tune. Along with the theory and terminology of WDO, a numerical study for tuning the WDO parameters is presented. WDO is further applied to three electromagnetics optimization problems, including the synthesis of a linear antenna array, a double-sided artificial magnetic conductor for WiFi applications, and an E-shaped microstrip patch antenna. These examples suggest that WDO can, in some cases, out-perform other well-known techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) or Differential Evolution (DE) and that WDO is well-suited for problems with both discrete and continuous-valued parameters.

Null Synthesis of Time-Modulated Circular Antenna Arrays Using an Improved Differential Evolution Algorithm

An efficient variant of differential evolution (DE) algorithm, namely subpopulated differential evolution (subDE), is proposed for solving null synthesis problems of time-modulated circular antenna arrays by controlling time intervals and phases. The capabilities of subDE algorithm are examined by comparing its convergence curves and number of successful optimizations to those of the classical DE. Wilcoxon rank-sum test is also applied to ensure that the results are significant in terms of statistics. Furthermore, the antenna array parameters achieved by using subDE are compared to those of the classical DE in the literature. The results show that subDE can exhibit better performance than the classical DE for our antenna array synthesis examples. Additionally, the simulations are executed on an embedded microprocessor to investigate if subDE can also run on such a limited environment. The results demonstrate that the contemporary embedded systems hold promise for evolutionary algorithms.

Elliptical Antenna Array Pattern Synthesis with Fixed Side Lobe Level and Suitable Main Lobe Beam width by Genetic Algorithm

In this paper, the design of uniform elliptical array (UEA) with optimum side lobe level reduction is presented. Multi-lobe pattern and adaptive nulling of the pattern is achieved by the control of the antenna elements phases in different states. This method is based on genetic algorithm (GA). The method of genetic algorithm is used to determine an optimum set of array factor cost that provide a radiation pattern with maximum side lobe level reduction with constraint of a suitable main lobe beamwidth. The results show that synthesis of the uniform elliptical antenna array by using GA method provide a side lobe level reduction and main lobe beamwidth better than circular antenna array obtained by using IWO (Invasive Weeds Optimization) and also optimized elliptical antenna array by using EPL (The Excitations Of Elements Phases at Eccentricity Low Level).

An Innovative Strategy for Synthesis of Uniformly Weighted Circular Aperture Antenna Array Based on the Weighting Density Method

Uniformly weighted planar array with a low peak sidelobe level is desired in many engineering applications. In this letter, an innovative strategy for synthesis of uniformly weighted circular aperture array in order to obtain a low peak sidelobe level is presented. This method is based on weighting density (WD) of an array, which refers to the average areal distribution of amplitude taper. By using WD of the reference array, the optimum radius or rings of desired array can be searched. Two types of uniformly weighted circular aperture arrays are applied with this method, and simulation results show a low peak sidelobe level as well as symmetric element distribution can be achieved.

Comparative Performance of RGA and BAT Algorithms in Location Only Null Synthesis of Circular Antenna Arrays

Circular antenna array pattern optimization for null performance improvement is carried out in this paper. Array geometries optimized for element locations in one elevation plane are found to provide good null performance uniformly for all elevation planes if the inter-element linear separations are kept within [0.5, 1] 0  . Optimizations for element locations have been carried out using Real Coded GA and BAT Algorithms independently. 

Synthesis of Two-Dimensional Antenna Array Using Independent Compression Regions

The synthesis of two-dimensional antenna arrays that allows to optimize the number of its elements is of great interest for long term evolution (LTE)-advanced wireless systems. In this communication we present a novel synthesis approach which focuses on reducing the number of antenna elements using independent compression regions (ICR). We base our approach on the non-iterative matrix pencil method (MPM) and the iterative Bayesian compressive sampling (BCS) method. Both of these techniques have been previously used for the compression of linear arrays and now we apply them in the context of two-dimensional arrays. Our compression method is based on the idea of segmenting the array in independent regions. A set of numerical experiments (small and large 2D arrays, shaped-beam antenna patterns) are presented to assess the performance and potentialities of ICR design approach.

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

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.

MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM FOR PATTERN SYNTHESIS OF ANTENNA ARRAYS

A modifled difierential evolution algorithm (MDE) for pattern synthesis of antenna arrays is proposed in this paper. By employing the novel strategies of best of random mutation and randomized local search, the convergence of standard difierential evolution algorithm (SDE) is signiflcantly accelerated. Five standard benchmark functions are optimized to testify the proposed algorithm by comparison with several other optimization algorithms. The numerical results verify the superior performance of the proposed MDE. Furthermore, the MDE is applied to two pattern synthesis examples, including a linear array and a cylindrical conformal array. Experiment results demonstrate that the proposed MDE has better performance than the other optimization methods in both of these two examples, which indicate the proposed algorithm is a competitive optimization algorithm in pattern synthesis.

Influence of Mutual Coupling and Current Distribution Errors on Advanced Phased Antenna Array Nulling Synthesis

Phased antenna array synthesis procedures based on the amplitude-phase and only-phase distributions providing the side lobe cancellation in a required direction are presented. A receiving antenna array was considered. It is characterized by the direction of the main beam for receiving the useful signal and the additional nulling direction. The required amplitude—phase distribution along the array is provided by the phase shifters and controllable attenuators/amplifiers. Moreover the modified synthesis procedure that takes into account the mutual coupling influence in the antenna array was proposed. Finally the radiation pattern transformation under the influence of the current distribution errors connected with a quality of phase shifters and attenuators/amplifiers was investigated.

Minimum Redundancy MIMO Array Synthesis by means of Cyclic Difference Sets

Antenna array synthesis is an important issue in MIMO radars. By judiciously designing antenna positions, one can create a very long virtual array steering vector with a small number of antennas and therefore achieve very high spatial resolution at a small cost. This paper presents a combinatorial methodology based on cyclic difference sets (CDSs) for minimum redundancy (MR) MIMO array synthesis which seeks to maximize the virtual array aperture for a given number of antennas. First, the key features of CDSs and the CDS-based MR-MIMO layouts are described. Then, the analytical expression of the maximum contiguous virtual array aperture is derived. Further, based on this expression, an enumerative shifting procedure is developed for identifying the optimal CDS-based MR-MIMO layout. Selected examples are analyzed to point out the computational effectiveness of the CDS-based MR-MIMO array synthesis.