Comparison of Evolutionary Algorithms for Synthesis of Non-Uniformly Spaced Linear Array of Unequal Length Parallel Dipole Antennas for Impedance Matching with low side lobe level

This work presents a comparative study of three evolutionary algorithms such as quantum particle swarm optimization (QPSO), firefly algorithm (FA) and cuckoo search algorithm (CS) for synthesis of linear array of non-uniformly spaced parallel unequal length very thin dipole antennas for impedance matching of all the antenna elements of an array with low side lobe level. Performance of the above three algorithms for impedance matching are compared here in terms of side lobe level as well as statistical parameters such as global best fitness value, worst fitness value, mean and standard deviation. Mutual coupling effect exists between the parallel dipole antennas and it is analyzed by induced electro-motive force (EMF) method, assuming Current distribution on each dipole to be sinusoidal. In addition to it, the obtained results from simulation of the entire optimization algorithm on Matlab is also validated by results obtained from FEKO analysis. One example is presented to show the effectiveness of the proposed approach. Moreover the applied method seems very effective for a linear array of dipole antennas; however, the principle can easily be extended to other type of arrays

Thinning of concentric two-ring circular array antenna using fire fly algorithm

AbstractThe paper describes the application of novel meta-heuristics of the fire fly algorithm for reduction of the maximum Side Lobe Level (SLL) with specific First Null Beam Width (FNBW) of thinned two-ring Uniform Concentric Circular Arrays (UCCA) of isotropic elements. The effect of thinning is analyzed in the four subsequent examples using uniform and non-uniform excitations for different FNBW. Optimization is carried out without and with prefixing the value of the percentage of thinning. The UCCA containing 35 and 70 elements in the two successive concentric rings is optimized using FFA. The example using non-uniform excitation is proved more efficient to reduce SLL for same FNBW. Simulation results show the SLL performance improves as we chose the FNBW wider in the designing problem. Fixing the percentage of thinning at a higher value increases the power efficiency of the feeding network with little compromise on the design specifications. The non-uniformly excited thinned concentric array is again optimized using two more state-of-the-art algorithms, namely, Particle Swarm Optimization (PSO) and Differential Evolution (DE) to compare the effectiveness of each algorithm in a statistically meaningful way. Design results using fire fly algorithm shows better performances compared to PSO and DE provided the same number of function evaluation has been considered for all the algorithms

QPSO for failure correction of linear array of mutually coupled parallel dipole antennas with desired side lobe level and return loss

A method based on quantum particle swarm optimization is proposed for correcting radiation pattern of a uniformly spaced linear array of parallel half-wavelength vertical very thin dipole antennas when more than one element of the array is completely defective. The generated pattern is broadside in the horizontal plane. Mutual coupling between the half-wavelength parallel dipole antennas has been taken care of by induced EMF method considering the current distribution on each dipole to be sinusoidal. Side lobe level and minimum return loss of the corrected pattern with defective elements are also calculated and an attempt is made that these parameters be equal to their respective specified values. This is usually done by changing excitation current amplitude of the non-defective elements without replacing the faulty elements. The element pattern of half-wavelength dipole antenna has been assumed omni-directional in the horizontal plane. Two examples are presented to show the effectiveness of the proposed approach