Fast and Optimal Design of a K-Band Transmit-Receive Active Antenna Array

Abstract

Abstract-An active-antenna array with 18 transmit elements and 18 receive elements is designed and fabricated. This T/R array can work at two different frequencies (19.5 GHz and 21.5 GHz) with multiple levels of isolation between the transmit and receive channels. A hybrid element-level vector finite element and adaptive multilevel fast multipole method (ELVFEM/AMLFMA) is applied to simulation the performance parameters of the array element and the full array fast. To obtained the maximum directivity of the array, the best distances of the T/R elements in the array are optimized by using the genetic algorithm (GE) combining with VFEM/AMLFMA. The design efficiency of the array is improved at a ratio of 30%. Finally the performance of the T/R array fabricated is measured in experiments and some good results are obtained.

Development of 61-Channel Digital Beamforming (Dbf) Transmitter Array for Mobile Satellite Communication

“…Standard hexagonal array can reduce the amount of antenna elements by 13.4% when the radiated beams of antenna appear in conical area perpendicular to the array, which has been proved by Sharp [8,9]. SHA consists of 61 microstrip patch elements, which are printed on dielectric substrate, with electrical characteristics ε r = 8.8, tan δ = 0.0022 and thickness h = 2 mm.…”

Large Phased Arrays Diagnostic via Distributional Approach

“…With these approaches one can determine the excitation coefficients of each radiating element and detects the failures by comparing the reconstructed ones with the nominal currents. Several deterministic and stochastic techniques have been developed [4][5][6][7][8][9] in the last years. Among the stochastic approaches, we point out the learning algorithms based on examples, such as neural networks [4,5], and the genetic algorithms based approaches [6,7].…”

“…Several deterministic and stochastic techniques have been developed [4][5][6][7][8][9] in the last years. Among the stochastic approaches, we point out the learning algorithms based on examples, such as neural networks [4,5], and the genetic algorithms based approaches [6,7]. These methods have the advantage to require small amount of samples of the radiated field and, in many cases, only amplitude data [7], but, due to the high size of search space, they can have poor performances.…”

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