Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
Abstract :
Genetic algorithms (GA) have been used for the design of electrically small wire antennas. From our previous work (Choo et al., IEEE Antennas and Propag. Soc. Int. Symp., p.330-3, 2002), we found that, for very small monopole antennas, the GA-optimized wire shapes take on a unique feature, namely, a point along the wire is shorted to the ground plane. It is interpreted that this turns the first portion of the wire structure into an inductive feed; the remaining portion becomes the radiating part of the antenna. The GA favors this inductive coupling mechanism to increase the input resistance for electrically small antennas. We explore this unique feature further by studying 2D planar antenna geometries that facilitate practical implementation, namely, the meander-shaped winding and the spiral-shaped winding. A Pareto GA is used to optimize the wire winding and feed configurations, taking into consideration size, bandwidth and efficiency. Several GA designs were built and measured to verify the GA results. A simple lumped-element circuit model is proposed to explain the inductively coupled feed mechanism. The optimized antenna configuration was implemented using a printed structure. Except for a slight shift in the resonant frequency, the printed antennas exhibited similar performance as the wire designs.
Keywords :
antenna feeds; equivalent circuits; genetic algorithms; microstrip antennas; monopole antennas; spiral antennas; wire antennas; electrically small antennas; genetic algorithm; inductive coupling; inductively coupled feed; input resistance; lumped-element circuit model; meander-shaped winding; monopole antennas; planar antennas; printed antennas; spiral-shaped winding; Algorithm design and analysis; Antenna accessories; Antenna feeds; Electric resistance; Genetic algorithms; Geometry; Pareto optimization; Planar arrays; Shape; Wire;