Synthesis and analysis of multi‐mode profile horn using mode matching technique and evolutionary algorithm

Abstract

This study presents the design and analysis of linear as well as cubic spline interpolated profiled smooth‐wall multimode horn using mode matching (MM) technique along with genetic algorithm (GA) and particle swarm optimisation (PSO). To apply the MM technique, the smooth profile conical geometry is assumed to consist of cascaded sections of large number of small symmetrical radial steps. Scattering matrix for each section has been calculated using MM technique and over all scattering matrix of the cascaded junctions has been calculated using generalised scattering matrix technique. The radiation pattern has been calculated using hybrid boundary contour mode matching technique. Optimisation of the linear/spline profile horn has been carried out using GA as well as PSO. Detailed modal analysis along with the convergence of the present technique for the smooth profile structure has also been carried out. A spline profile multimode horn working at 89 GHz has been designed and developed. The present analysis has been verified with the measured results. There is a very good agreement between theoretical and measured results.

AIT Inversion and Site Applications Using Various Forward Algorithms

“…Another method to calculate AIT responses is NMM method [6][7][8]. The numerical analysis was used in the radial direction and analysis method was adopted in the vertical direction.…”

“…In order to eliminate the environmental influence and obtain the true-formation resistivity, a fast inversion technique was suggested in the present study. Since the inversion calculation was dependent on the forward algorithm, two forward calculation algorithms, geometry factor (GF) theory [1] and numerical mode-matching (NMM) method [6][7][8], were used in the inversion calculation respectively.…”

Antenna Design by Means of the Fruit Fly Optimization Algorithm

“…Nevertheless, modern computational power allows the use of heuristic or evolutionary techniques such as the Genetic Algorithm (GA) [1][2][3][4][5], Ant Colony Optimization (ACO) [6][7][8], Particle Swarm Optimization (PSO) [9][10][11][12], or Gravitational Search Algorithm (GSA) [13,14] among others. These algorithms are especially suited for problems where the derivative of the cost function is unknown or not easily computed.…”

“…Specifically, the FOA will be first applied to the problem of synthesizing an array factor (as an initial validation example) and then to the more complex case of the optimization of horn antenna profiles, which are of primary interest in the front-end of modern communication systems [3,4]. To the best of the authors' knowledge the FOA has not been applied to complex radiation problems like these, which require full wave simulations.…”