Uniform Inter-element Spacing Research Articles

English

In this work, the cockroach swarm optimization (CSO) technique was investigated for its potential to reduce side lobe levels of an array of linear antennae. This optimization technique is applied for antenna synthesis for the first time by the authors. Variations in the excitation phase, number of elements, and inter-element spacing were also investigated to determine their effects on the antenna's side lobe level (SLL). The objective of this work is to optimize the inter-element distance and the strength of the excitation signal using Cockroach Swarm Optimization. In order to achieve this goal, an objective function was developed for optimizing antenna parameters. MatLab was used to generate the cockroach swarm optimization algorithm. Excitation amplitude, inter-element spacing, and phase are the optimal antenna parameters that were considered. The research findings show that the side lobe level is minimized at an inter-element spacing of 0.5, which is in tandem with results obtained from literature using another analytical and numerical approach. The proposed CSO algorithm achieves peak SLL values of -13.10, -17.26, -24.14, and -28.05 dB for uniform inter-element spacing and excitation phase when 4, 8, 12, and 16 antenna elements are selected, respectively. Minimum HPBW values are 15 degrees, 11 degrees, 9 degrees, and 7 degrees. Not only were side lobes reduced, but the beam's breadth was also drastically reduced by 15%. The beam's diameter was narrowed to show increased directivity while the sidelobe level was decreased. For the number of elements N=16, the SLL is decreased by 1.29 dB, and the HPBW is decreased by 2° compared to particle swarm optimization. In the case of N = 12, reductions of 0.8 dB in SLL and 2° in HPBW are seen. The SLL and HPBW both decrease by 1.29 dB and 2° for N = 16. Also, when N=4, SSL= -17.1, HPBW=15°, N=8, SSL=-19.1 HPBW=12°. The research findings may find application in creating low-processing-burden smart antenna design.

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

Unlike conventional phased array (PA), frequency diversity array (FDA) can perform the beampattern synthesis not only in an angle dimension but also in a range dimension by introducing an additional frequency offset (FO) across the array aperture, thus greatly enhancing the beamforming flexibility of an array antenna. Nevertheless, an FDA with uniform inter-element spacing that consists of a huge number of elements is required when a high resolution is needed, which results in a high cost. To substantially reduce the cost while almost maintaining the antenna resolution, it is important to conduct a sparse synthesis of FDA. Under these circumstances, this paper investigated the transmit-receive beamforming of a sparse-fda in range and angle dimensions. In particular, the joint transmit-receive signal formula was first derived and analyzed to resolve the inherent time-varying characteristics of FDA based on a cost-effective signal processing diagram. In the sequel, the GA-based low sidelobe level (SLL) transmit-receive beamforming of the sparse-fda was proposed to generate a focused main lobe in a range-angle space, where the array element positions were incorporated into the optimization problem. Numerical results showed that 50% of the elements can be saved for the two linear FDAs with sinusoidally and logarithmically varying frequency offsets, respectively termed as sin-FO linear-FDA and log-FO linear-FDA, with only a less than 1 dB increment in SLL. The resultant SLLs are below -9.6 dB, and -12.9 dB for these two linear FDAs, respectively.

An Efficient Conformal Stacked Antenna Array Design and 3D-Beamforming for UAV and Space Vehicle Communications.

In this paper, a new conformal array structure and beamforming technique are proposed to provide efficient communication performance for unmanned aerial vehicles (UAVs) and space vehicles. The proposed array is formed by conformally stacking cylindrical, conical, and concentric circular (CSC4) arrays which are all coaxially aligned with the same axis of the conformed body and with uniform interelement spacing. The array elements are then fed by a weighting vector that has an adaptive cosine tapered profile where the maximum amplitude coefficient is oriented with the mainlobe direction to improve the scanning capabilities of the array and increase the array effective area. In addition, for very large, conformed body structures such as space vehicles, a frontal mainlobe-oriented partial CSC4 array beamforming technique is proposed to efficiently utilize the large CSC4 structure, reduce the processing requirements for mainlobe electronic steering, and to provide very low sidelobe levels with reduced backlobe levels. Simulation results show that the proposed CSC4 design can provide wide scanning angles of up to angular range in the -direction with only change in the beamwidth, without increasing array size and with achievable sidelobe level of −45 dB and backlobe levels less than −10 dB.

Deterministic Synthesis Approach for Linear Sparse Array Antennas

This article discusses a deterministic technique for the synthesis of isophoric (equally fed) linear sparse array antennas (LSAAs) consisting of nonuniform (aperiodic) placement of the radiating elements on the array aperture. This article derives nonequal interelements spacing in LSAA for demonstrating low sidelobe level (SLL) with equally fed elements. The deterministic approach is called as Array Dilation Technique (ADT). It stretches the array in analogy to an elastic membrane and henceforth, creating an aperiodicity in the array. This technique does not require any model taper and simply takes a uniformly fed array with uniform interelement spacing as the initial array subjected to the application of ADT. The technique demonstrates achieving comparatively lower SLL for optimal thinning levels in comparison to the prior published literature. The numerical case studies presented are compared with the previous literature demonstrating the effectiveness and the outperformance of the newly proposed technique.

Closed-Form Expression for First Null Beamwidth of a Beam-Steered Dolph–Tschebysheff Array

ABSTRACTIn this article, a closed-form expression for the first null beamwidth of a beam steered Dolph–Tschebysheff linear array antenna has been presented, where the number of elements, uniform inter-element spacing, side lobe level (in dB), and steering angle are considered as design parameters. Accordingly, the limitation in the beam-steering capability of a Dolph–Tschebysheff linear array has been modeled computationally. First null beamwidth values obtained using the proposed formula has been compared with that obtained from a conventional array factor plot. Results shows at least 95% accuracy in predicting the value of first null beamwidth and maximum steering angle under particular design constraints showing the effectiveness of the proposed formulas.

Directivity improvement and optimal far field pattern of time modulated concentric circular antenna array using hybrid evolutionary algorithms

In this paper time modulated nine-ring concentric circular antenna array (TMCCAA) using fitness based novel hybrid adaptive differential evolution with particle swarm optimization (ADEPSO) has been studied. ADEPSO is hybrid of fitness based adaptive differential evolution and particle swarm optimization (PSO). Differential evolution is a simple and robust evolutionary algorithm but sometimes causes instability problem; PSO is also a simple, population based robust evolutionary algorithm but has the problem of sub-optimality. ADEPSO has overcome the above individual disadvantages faced by both the algorithms and is used for the design of TMCCAA. The comparative case studies as Case-1 and Case-2 are made with three control parameters like uniform inter-element spacing in rings, inter-ring radii and the switching “ON” times of rings. The same array radiates at various harmonic frequencies. The first two harmonic frequencies have been considered in this work. The numerical results show Case-2, outperforms Case-1 with respect to better side lobe level (SLL), and more improved directivity. Apart from this, the authors have computed powers radiated at the center/fundamental frequency and the first two sideband frequencies, and dynamic efficiency. It is found that power radiated by any sideband frequency is very less as compared with the power radiated at the center frequency. It has been observed that as the sideband frequency increases, side band level decreases to the greater extent as compared with SLL. The aperture size is a very important constraint for the array, since there is an upper limit for the aperture size of a given array in real-life environment. Hence, in our optimization design, the maximum radius of the concentric ring array is constrained.

CRPSOWM for Linear Antenna Arrays with Improved SLL and Directivity

ABSTRACTIn this paper, swarm-based algorithms craziness particle swarm optimization with wavelet mutation (CRPSOWM) have been applied for the optimal design of hyper beamforming of linear antenna array. The conventional gradient based optimization techniques are not efficient and get trapped on local optima for such multimodal highly non-linear constrained hyper beamforming optimization problem. Thus, the above evolutionary technique has been adopted. CRPSOWM incorporates a new definition of swarm updating with the help of wavelet theory. Wavelet mutation enhances the CRPSO to explore the solution space more effectively compared to the other optimization methods as reported in firefly algorithm (FFA). Thus CRPSOWM is apparently free from getting trapped at local optima and premature convergence. The simulation results show CRPSOWM outperforms FFA by achieving much greater reduction in side lobe level, improved directivity and much more improved first null beam width keeping the same value of hyper beam exponent. The optimized hyper beam is achieved by optimization of current excitation weights and uniform inter-element spacing. The approach is illustrated through 10-, 14-, and 20-element linear antenna arrays.

Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm

Teaching-learning-based optimization (TLBO) algorithm is a new kind of stochastic metaheuristic algorithm which has been proven effective and powerful in many engineering optimization problems. This paper describes the application of a modified version of TLBO algorithm, MTLBO, for synthesis of thinned concentric circular antenna arrays (CCAAs). The MTLBO is adjusted for CCAA design according to the geometry arrangement of antenna elements. CCAAs with uniform interelement spacing fixed at half wavelength have been considered for thinning using MTLBO algorithm. For practical purpose, this paper demonstrated SLL reduction of thinned CCAAs in the whole regular and extended space other than the phi = 0° plane alone. The uniformly and nonuniformly excited CCAAs have been discussed, respectively, during the simulation process. The proposed MTLBO is very easy to be implemented and requires fewer algorithm specified parameters, which is suitable for concentric circular antenna array synthesis. Numerical results clearly show the superiority of MTLBO algorithm in finding optimum solutions compared to particle swarm optimization algorithm and firefly algorithm.

Design of thinned concentric circular antenna arrays using firefly algorithm

Firefly algorithm (FA) is a nature inspired computing algorithm based on the behaviour of fireflies. It is a kind of stochastic meta-heuristic algorithm that can be used for various engineering optimisation problems. This study presents application of FA for the design of thinned multiple concentric circular antenna arrays. The aim is to achieve an array of uniformly excited isotropic elements that will generate a pencil beam pattern in the vertical plane with minimum side lobe level (SLL). Two different cases have been considered in this study for thinning of concentric circular (ring) arrays using FA. The first case is with uniform inter-element spacing fixed at 0.5λ or its multiple and the second case with optimum inter-element spacing or its multiple. The thinning percentage of the array is kept equal to or more than 50% and the beamwidth is kept equal to or less than that of a fully populated, uniformly excited and 0.5λ spaced ring array of same number of elements and rings. The results obtained are compared with previous published results, which show the effectiveness of this approach.

Synthesis of linear array using Taylor distribution and Particle Swarm Optimisation

In this article, non-uniformly excited linear arrays are optimised using Taylor distribution and classical particle swarm optimisation (CPSO) algorithm for obtaining desired equal side lobe level (SLL). Elements of the array are considered to be isotropic in nature with uniform interelement spacing. Excitation amplitudes of each element are taken as optimisation parameters. Taylor distribution defines the range of excitation amplitude in which CPSO algorithm searches for the optimum value of excitation amplitude, with the objective of obtaining desired equal SLL. The proposed method eliminates the initial randomness of defining search space for CPSO algorithm. Comparison with other methods has been made whenever possible. The results reveal that the proposed method can be used to obtain the desired SLL.

DECOMPOSITION-BASED EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION APPROACH TO THE DESIGN OF CONCENTRIC CIRCULAR ANTENNA ARRAYS

We investigate the design of Concentric Circular Antenna Arrays (CCAAs) with ‚=2 uniform inter-element spacing, non-uniform radial separation, and non-uniform excitation across difierent rings, from the perspective of Multi-objective Optimization (MO). Unlike the existing single-objective design approaches that try to minimize a weighted sum of the design objectives like Side Lobe Level (SLL) and principal lobe Beam-Width (BW), we treat these two objectives individually and use Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) with Difierential Evolution (DE), called MOEA/D-DE, to achieve the best tradeofi between the two objectives. Unlike the single-objective approaches, the MO approach provides greater ∞exibility in the design by yielding a set of equivalent flnal (non- dominated) solutions, from which the user can choose one that attains a suitable trade-ofi margin as per requirements. We illustrate that the best compromise solution attained by MOEA/D-DE can comfortably outperform state-of-the-art variants of single-objective algorithms like Particle Swarm Optimization (PSO) and Difierential Evolution. In addition, we compared the results obtained by MOEA/D-DE with those obtained by one of the most widely used MO algorithm called NSGA-2 and a multi-objective DE variant, on the basis of the R- indicator, hypervolume indicator, and quality of the best trade- ofi solutions obtained. Our simulation results clearly indicate the superiority of the design based on MOEA/D-DE.

Optimized Hyper Beamforming of Linear Antenna Arrays Using Collective Animal Behaviour

A novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied for the optimal design of hyper beamforming of linear antenna arrays. Hyper beamforming is based on sum and difference beam patterns of the array, each raised to the power of a hyperbeam exponent parameter. The optimized hyperbeam is achieved by optimization of current excitation weights and uniform interelement spacing. As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. Again, further reductions of sidelobe level (SLL) and first null beam width (FNBW) have been achieved by the proposed collective animal behaviour (CAB) algorithm. CAB finds near global optimal solution unlike RGA, PSO, and DE in the present problem. The above comparative optimization is illustrated through 10-, 14-, and 20-element linear antenna arrays to establish the optimization efficacy of CAB.

Design of Non-Uniform Antenna Arrays Using Genetic Algorithm

The performance of a single-element antenna is somewhat limited. To obtain high directivity, narrow beamwidth, low side-lobes, point-to-point and preferred-coverage pattern characteristics, etc., antenna arrays are used. An antenna array is an assembly of individual radiating antennas in an electrical and geometrical configuration. Nowadays, antenna arrays appear in wireless terminals and smart antennas, so robust and efficient array design is increasingly becoming necessary. In antenna array design, it is frequently desirable to achieve both a narrow beamwidth and a low side-lobe level. In linear antenna arrays, a uniform array (having uniform inter-element spacing and uniform amplitude excitation) yields the smallest beamwidth and hence the highest directivity. It is followed, in order, by the Dolph-Chebyshev and Binomial arrays. In contrast, Binomial arrays usually possess the smallest side-lobes followed, in order, by the Dolph-Chebyshev and uniform arrays. Binomial and Dolph-Chebyshev arrays are typical examples of non-uniform arrays. Non-uniform linear antenna arrays have uniform inter-element spacing and non-uniform amplitude distributions. In this paper we deal only with linear arrays and it is shown that using genetic algorithm it is possible to design a non-uniform array that approximates the beamwidth of a uniform array and having smaller side-lobe level than the Dolph-Chebyshev array. The result is that the designed antenna array exhibits the largest directivity as compared to the uniform, Binomial and Dolph-Chebyshev arrays. In the design, the genetic algorithm is employed to generate the excitation amplitudes of the antenna array.

SYNTHESIS OF THINNED PLANAR CONCENTRIC CIRCULAR ANTENNA ARRAYS --- A DIFFERENTIAL EVOLUTIONARY APPROACH

Circular antenna array design is one of the most important electromagnetic optimization problems of current interest. The problem of designing a large multiple concentric planar thinned circular ring arrays of uniformly excited isotropic antennas is considered in this paper. This antenna must generate a pencil beam pattern in the vertical plane along with minimized side lobe level (SLL). In this paper, we present an optimization method based on an improved variant of one of the most powerful real parameter optimizers of current interest, called Difierential Evolution (DE). Two sets of difierent cases have been studied here. First set deals with thinned array design with the goal to achieve number of switched ofi elements equal to 220 or more. The other set contains design of array while maintaining side lobe level (SLL) below a flxed value. Both set contains two types of design, one with uniform inter-element spacing flxed at 0.5‚ and the other with optimum uniform inter-element spacing. The half-power beam width of the synthesized pattern is attempted to maintain flxed at the value equal to that of a fully populated array with uniform spacing of 0.5‚. Simulation results of the designed thinned arrays are compared with a fully populated array for all the cases to illustrate the efiectiveness of our proposed method.

SYNTHESIS OF THINNED PLANAR CIRCULAR ARRAY ANTENNAS USING MODIFIED PARTICLE SWARM OPTIMIZATION

In this paper, the authors present an optimization method based on modifled Particle Swarm Optimization (PSO) algorithm for thinning large multiple concentric circular ring arrays of uniformly excited isotropic antennas that will generate a pencil beam in the vertical plane with minimum relative side lobe level (SLL). Two difierent cases have been studied, one with flxed uniform inter-element spacing and another with optimum uniform inter-element spacing. In both the cases, the number of switched ofi elements is made equal to 220 or more. The half- power beam width of the synthesized pattern is attempted to make equal to that of a fully populated array with uniform spacing of 0:5‚. Simulation results of the proposed thinned arrays are compared with a fully populated array to illustrate the efiectiveness of our proposed method.

Wideband MVDR beamforming for acoustic vector sensor linear array

A wideband minimum variance distortionless response (MVDR) beamforming approach for an acoustic vector sensor linear array is presented, which is based on coherent signal subspace preprocessing, to solve the problem of direction of arrival (DOA) estimation for wideband coherent acoustic sources. The concept of wideband focusing is introduced into wideband processing for the acoustic vector sensor array, and the relationship between the wideband focusing matrices of the acoustic vector sensor array and the pressure sensor array is derived. Simulation results show that wideband MVDR beamforming of an acoustic vector sensor linear array outperforms that of a pressure sensor when dealing with wideband coherent sources, in the following aspects: realising unambiguous direction finding in the whole space, i.e. no left/right ambiguity problem; allowing the uniform interelement spacing to exceed the Nyquist half-wavelength upper limit; and having a better performance for DOA estimation when dealing with sources close to endfire.