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Optimized hyper beamforming of receiving linear antenna arrays using Firefly algorithm gopi ram 1 , durbadal mandal 1 , rajib kar 1 and sakti prasad ghoshal 2In this paper, an optimized hyper beamforming method is presented based on a hyper beam exponent parameter for receiving linear antenna arrays using a new meta-heuristic search method based on the Firefly algorithm (FFA). A hyper beam is derived from the sum and difference beam patterns of the array, each raised to the power of a hyper beam exponent parameter. As compared to the conventional hyper beamforming of the linear antenna array, FFA applied to the hyper beam of the same array can achieve much more reduction in sidelobe level (SLL) and improved first null beam width (FNBW), keeping the same value of the hyper beam exponent. As compared to the uniformly excited linear antenna array with interelement spacing of l/2, conventional non-optimized hyper beamforming and optimal hyper beamforming of the same obtained by real-coded genetic algorithm, particle swarm optimization and Differential evolution, FFA applied to the hyper beam of the same array can achieve much greater reduction in SLL and same or less FNBW, keeping the same value of the hyper beam exponent parameter. The whole experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.

In this paper, a 9-ring time modulated concentric circular antenna array (TMCCAA) with isotropic elements has been studied based on an evolutionary optimization algorithm called cat swarm optimization (CSO) for the reduction of side lobe level and improvement in the Directivity, simultaneously. The comparative case studies as Case-1 and Case-2 are made with three control parameters like inter-element spacing in rings, inter-ring radii and the switching "ON" times of rings with the help of same algorithm. Experimental results show a considerable side lobe level reduction with respect to the uniformly excited case. The numerical results show Case-2 outperforms Case-1 with respect to side lobe level (SLL) and Directivity. Apart from this, the powers radiated at the center/fundamental frequency and the first two sideband frequencies, and dynamic efficiency have been computed. It has been observed that as the sideband frequency increases, both the powers radiated by harmonic frequencies and side band levels (SBL) decrease.

Optimal pulse shifting in timed antenna array for the reduction of sidelobe and sideband using improved harmony search algorithm (IHSA) dealt in this paper. The essence of 'Time-modulation' lies in the fact that 'Time' can be used as an additional control parameter in antenna array synthesis. The proposed approach demonstrates the controlling nature of periodic time sequences through pulse shifting. The undesired sideband radiations (SRs) generated in time modulated linear array (TMLA) is controlled by minimizing the sideband levels (SBLs) with an optimal pulse shifting scheme applied to the outer elements of the array. Evolutionary algorithm-based design is considered to optimize the time sequences and the excitation coefficients of the array along with the inter-element spacing between the array elements for sidelobe level (SLL) reduction at the fundamental frequency. Pulse shifting with optimized switch-ON instants and switch-ON time intervals of outer elements is responsible for the minimization of SBL only, as the fundamental pattern does not depend on pulse shifting. Thus, a combined approach is developed with optimized excitation coefficients and controlled pulse switching to reduce the SLL and SBL of TMLA simultaneously. 16 and 30 isotropic elements of TMLA structures are considered with a music-inspired IHSA to get the optimal solution. IHSA based numerical results are compared with the results obtained from other applied algorithms such as harmony search algorithm (HSA), particle swarm optimization (PSO), and real-coded genetic algorithm (RGA) with the proposed pulse shifting scheme. The obtained numerical results are also compared with previously published literature results to show the superior performance achieved by the proposed approach.

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.