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In this paper, a novel approach for synthesizing multiple radiation patterns with reduced hardware complexity in the feed network by exploiting the additional degree of freedom ‘time’ in time modulated unequally spaced linear array (TMUSLA) is presented. In the proposed approach, with a suitable common set of element position of TMUSLA, the desired dual-beam pattern with low sidelobe level (SLL) is obtained by simply controlling the ON-OFF time sequence of the RF switches connected to the array elements. To show the effectiveness of the proposed array synthesis method, two dual beam patterns - first one as pencil (sum) beam (PB) and flat-topped beam (FTB) pattern, and the second one as sum and difference pattern with different constraints have been synthesized. For the successful generation of the desired power patterns, differential evolution (DE) algorithm is employed to obtain the optimum possible solution in terms of common element position, time-modulation, switching sequences and applicable excitation phase for the desired shape beam patterns. The superiority of the proposed approach with the favourable improved performance have been demonstrated by comparing the realized patterns with the state-of-the-art relevant reported works.

A novel method of designing unequally spaced time-modulated arrays (UESTMAs) by handling fewer optimization parameters with reduced problem dimension is presented in this paper. For synthesizing UESTMA, two design parameters, specifically, the non-linear parameter - element position, and the linear parameter – on-time durations are optimized in two steps. Different possible cases of linear and non-linear synthesis methods such as, position-only (PO), on-time only (OTO), position then on-time (PTOT), on-time then position (OTTP), and simultaneous position on-time (SPOT) are considered. To examine the performance of the synthesis methods, three global search stochastic algorithms based on differential evolution (DE), teaching-learning-based optimization (TLBO) and quantum particle swarm optimization (QPSO) have been employed to achieve the array pattern with significantly suppressed side lobe levels and sideband levels. Through comparative study, it is observed that the two step non-liner to linear synthesis method by fewer optimization parameters is efficient to provide better pattern with less computation time.

This paper describes the synthesis of digitally excited pencil/flat top dual beams simultaneously in a linear antenna array constructed of isotropic elements. The objective is to generate a pencil/flat top beam pair using the excitations generated by the evolutionary algorithms. Both the beams share common variable discrete amplitude excitations and differ in variable discrete phase excitations. This synthesis is treated as a multi-objective optimization problem and is handled by Quantum Particle Swarm Optimization algorithm duly controlling the fitness functions. These functions include many of the radiation pattern parameters like side lobe level, half power beam width and beam width at the side lobe level in both the beams along with the ripple in the flat top band of flat top beam. In addition to it, the dynamic range ratio of the amplitudes excitations is set below a certain level to diminish the mutual coupling effects in the array. Two sets of experiments are conducted and the effectiveness of this algorithm is proved by comparing it with various versions of swarm optimization algorithms.

This paper presents a new approach for circular array of parasitic dipoles composed by one active dipole for reduction of side lobe level with maximum directivity including mutual coupling. The desired goal is obtained by changing the spacing between the parasitic elements and length of the parasitic elements while the position and length of driven element is fixed. In addition to it, reflection coefficient (RC) of the driven element is kept closer to the specified value. Matlab based method of moment code is used to evaluate the performance of circular antenna designs generated by QPSO algorithm. Two examples are presented to show the effectiveness of this proposed approach.

In this paper, the authors have proposed a method based on Quantum Particle Swarm Optimization (QPSO) algorithm in the context of radiation pattern correction of a linear array of isotropic antennas corrupted with one or more faulty antenna elements. Care is taken to maintain the values of side lobe level and maximum Wide Null Placement of the corrected pattern to be identical to the values of non-defective radiation pattern. This correction is made possible by altering the beam weights of the remaining elements in the array. The advantage of this method is that the necessity of replacement of the faulty elements is eliminated. Simulation is done on the linear antenna array constructed of individual isotropic elements separated by identical inter-element spacing and the results obtained from the simulation depict the effectiveness of the proposed method. This method can also be extended to other array geometries.

A method based on constricted Particle Swarm Optimization (CPSO) algorithm to design a non-uniformly spaced collinear array of thin dipole antennas of unequal height is proposed. This paper presents a method for computing the appropriate excitation and geometry of individual array elements to generate a pencil beam in the vertical plane with minimum Standing Wave Ratio (SWR) and fixed Side Lobe Level (SLL). Coupling effect between any two collinear center-fed thin dipole antennas having sinusoidal current distributions is analyzed using induced EMF method and minimized in terms of SWR. DRR of excitation distribution is fixed at a lower value for further mitigation of the coupling effect. Phase distribution for all the elements is kept at zero degree for broadside array. Optimization results show the effectiveness of the algorithm for the design of the array. Moreover method seems very conducive for estimating the mutual impedance between any two collinear center-fed thin dipole antennas having sinusoidal current distributions.