Optimum Side Lobe Level Research Articles

Performance Analysis of Dolph-Tschebyscheff Array for Different SLL and Array Length

A comprehensive analysis on performance of Dolph-Tschebyscheff distribution for different array length and side lobe levels has been presented in this paper. Dolph-Tschebyscheff array, which is a compromise between binomial and uniform array, produces optimum side lobe level, efficiency, and half power beamwidth, hence, it is referred to as optimum distribution. For a larger number of elements, the Tschebyscheff array demands higher side lobe suppression in order to avoid the abrupt amplitude distribution at the edges that results from more elements and lower side lobe suppression, at the same time, higher side lobe suppression decreases aperture efficiency and gain. These novel analyses have been carried out by computing parameters such as power pattern, first side lobe level, directivity and half power beamwidth. Plots for optimum SLL and critical SLL are derived for a range of array elements, which defines three regions assisting in selection of appropriate number of elements and desired major-to-minor lobe levels for linear/planar array antenna designs. Practical array analysis is proposed by approximating the amplitude of arrays’ end elements, whenever it becomes higher than their adjacent elements.

Optimum design of both linear and planar sparse arrays with sidelobe level reduction using salp swarm algorithm

Sparse arrays play an important role in the widely used acoustic and electromagnetic applications such as sonar, radar, and satellite. In this paper, a recently proposed swarm intelligence algorithm, salp swarm algorithm (SSA), is introduced for design of both linear and planar sparse antenna arrays with optimum sidelobe level (SLL). The design of sparse antenna arrays can be regarded as a nonlinear optimization problem, which the main optimization goal is finding optimum excitations and positions for antenna elements to achieve antenna array beam pattern with desired SLL. The SSA is a new kind of swarm intelligence algorithm which inspired by the swarming behavior of salps. Compared to other evolutionary algorithms, the SSA requires few algorithm-specified tuning parameters, which makes it simple and easy to use for engineering. Illustrative examples of both linear and planar arrays are given to verify the validity of the SSA for SLL reduction of sparse arrays.

Design of planar concentric circular antenna arrays with reduced side lobe level using symbiotic organisms search

This paper investigates the design of concentric circular antenna arrays (CCAAs) with optimum side lobe level reduction using the Symbiotic Organisms Search (SOS) algorithm. Both thinned and full CCAAs are considered. SOS represents a rather new evolutionary algorithm for antenna array optimization. SOS is inspired by the symbiotic interaction strategies between different organisms in an ecosystem. SOS uses simple expressions to model the three common types of symbiotic relationships: mutualism, commensalism, and parasitism. These expressions are used to find the global minimum of the fitness function. Unlike other methods, SOS is free of tuning parameters, which makes it an attractive optimization method. The results obtained using SOS are compared to those obtained using several optimization methods, like Biogeography-Based Optimization (BBO), Teaching-Learning-Based Optimization (TLBO), and Evolutionary Programming (EP). It is shown that the SOS is a robust straightforward evolutionary algorithm that competes with other known methods.

Synthesis of thinned planar antenna arrays using teaching–learning-based optimization

In this paper, the design of thinned planar antenna arrays of isotropic radiators with optimum side lobe level reduction is studied. The teaching–learning-based optimization (TLBO) method, a newly proposed global evolutionary optimization method, is used to determine an optimum set of turned-ON elements of thinned planar antenna arrays that provides a radiation pattern with optimum side lobe level reduction. The TLBO represents a new algorithm for optimization problems in antenna arrays design. It is shown that the TLBO provides results that are better than (or the same as) those obtained using other evolutionary algorithms.

Design of non-uniform concentric circular antenna arrays with optimal sidelobe level reduction using biogeography-based optimization

This paper presents the design of non-uniform concentric circular antenna arrays (CCAAs) of isotropic radiators with optimum sidelobe level (SLL) reduction. The biogeography-based optimization (BBO) method is used to determine an optimum set of excitation amplitudes that provide a radiation pattern with optimum SLL reduction with the constraint of a fixed major lobe beamwidth. The BBO method represents a new global evolutionary algorithm for optimization problems in electromagnetics. It is shown that the BBO results provide an SLL reduction that is comparable to that obtained using well-known algorithms, such as the particle swarm optimization (PSO), genetic algorithm (GA), and evolutionary programming (EP). Moreover, BBO results are compared with those obtained using the Matlab function Fmincon which uses a sequential quadratic programming (SQP) method. The comparison shows that the design of non-uniformly excited CCAAs using the SQP method provides a SLL reduction that is better than that obtained using global stochastic optimization methods, indicating that global optimization techniques might not really be needed in this problem.

Synthesis of Non-Uniform Amplitude equally Spaced Antenna Arrays Using PSO and DE Algorithms

In recent years Evolutionary computation has its growth to extent. Synthesis of non-uniform linear antenna arrays is one of the most important electromagnetic optimization problems of the current interest. In this paper, the design of non-uniform linear antenna arrays with optimum side lobe level reduction is investigated. Two global evolutionary optimization methods are Particle Swarm Optimization algorithm(PSO) and Differential Evolution algorithm(DE ) are used to determine an optimum set of weights and positions that provide a radiation pattern with optimum side lobe level having uniform progressive phase between the elements. Simulation results show considerable enhancements in array performances using the global optimizers. The paper finally illustrates a comparative evaluation of the two proposed algorithms regarding their applicability as numerical optimization techniques.

Synthesis of thinned concentric circular antenna arrays using teaching-learning-based optimization

In this article, the design of thinned concentric circular antenna arrays CCAAs of isotropic radiators with optimum side lobe level SLL reduction is studied. The newly proposed global evolutionary optimization method; namely, the teaching-learning-based optimization TLBO is used to determine an optimum set of turned ON elements of thinned CCAAs that provides a radiation pattern with optimum SLL reduction. The TLBO represents a new algorithm for optimization problems in electromagnetics and antennas. It is shown that the TLBO provides results that are somewhat better than those obtained using other evolutionary algorithms, like the firefly algorithm and biogeography based optimization. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:443-450, 2014.

Circular antenna array synthesis using firefly algorithm

In this article, the design of circular antenna arrays (CAAs) and concentric circular antenna arrays (CCAAs) of isotropic radiators with optimum side lobe level (SLL) reduction is studied. The newly proposed global evolutionary optimization method; namely, the firefly algorithm (FA) is used to determine an optimum set of weights and positions for CAAs, and an optimum set of weights for CCAAs, that provides a radiation pattern with optimum SLL reduction with the constraint of a fixed major lobe beamwidth. The FA represents a new algorithm for optimization problems in electromagnetics. It is shown that the FA results provide a SLL reduction that is better than that obtained using well-known algorithms, like the particle swarm optimization, genetic algorithm (GA), and evolutionary programming. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:139–146, 2014.

Position‐only side lobe reduction of a uniformly excited elliptical antenna array using evolutionary algorithms

This study deals with the design of elliptical antenna arrays for specific radiation property using three different evolutionary algorithms; namely, self-adaptive differential evolution method, biogeography based optimisation method and firefly algorithm. These methods are used to determine an optimum set of positions for uniformly excited elliptical antenna array (EAA) that provides a radiation pattern with optimum side lobe level reduction with the constraint of a fixed major lobe beamwidth. Three examples are investigated; 8, 12 and 20 elements EAAs using these evolutionary algorithms. The comparison shows that the design of non-uniform EAAs using evolutionary algorithms presents a good side lobe reduction in the radiation pattern for the optimised design. Furthermore, the BBO method shows somewhat better performance compared with the other two methods.

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).

Linear Array Pattern Synthesis for Wide Band Sector Nulling

This paper presents a new technique for the synthesis of multiple wide band nulls by controlling the complex current excitations in linear arrays. The complex current excitations are determined using the minimax approximation approach to suppress multiple wide band sectors while maintaining the sidelobe level and the main beam width almost unchanged. This method estimates the required number of pattern nulls to realize the prescribed suppressed sectors and locates the positions of the remaining nulls to control the optimum sidelobe level for the perturbed pattern in the minimax sense. The results show the formation of single and multiple wide band nulls at arbitrary prescribed directions. Also, this method can impose arbitrary symmetric and asymmetric nulls in the sidelobe region and hence, overcome the limitations of the linearized amplitude-only or phase-only solutions.

Linear Array Pattern Synthesis for Wide Band Sector Nulling - Abstract

This paper presents a new technique for the synthesis of multiple wide band nulls by controlling the complex current excitations in linear arrays. The complex current excitations are determined using the minimax approximation approach to suppress multiple wide band sectors while maintaining the sidelobe level and the main beam width almost unchanged. This method estimates the required number of pattern nulls to realize the prescribed suppressed sectors and locates the positions of the remaining nulls to control the optimum sidelobe level for the perturbed pattern in the minimax sense. The results show the formation of single and multiple wide band nulls at arbitrary prescribed directions. Also, this method can impose arbitrary symmetric and asymmetric nulls in the sidelobe region and hence, overcome the limitations of the linearized amplitude-only or phase-only solutions.

Phase-only synthesis of minimum peak sidelobe patterns for linear and planar arrays

Minimization of the maximum sidelobe level for a given array geometry by phase-only adjustment of the element excitations is considered. Optimum phases are obtained by using a numerical search procedure to minimize the expression for the pattern sidelobe level with respect to the element phases. Results for both linear and planar arrays of equispaced elements are presented. The data suggests that optimum sidelobe level is a logarithmic function of array size, and optimum patterns have relative efficiencies that are typically somewhat greater than for comparable-amplitude tapered arrays. An analytic synthesis algorithm is presented for use on very large arrays for which the numerical search technique for the minimization of the sidelobe level is computationally impractical. This method produces patterns with characteristics similar to arrays synthesized using the numerical search method, i.e. relatively uniform angular distribution of energy in the sidelobe region, and generally decreasing maximum sidelobe level as the array size is increased. >