Evolutionary Optimization of Yagi-Uda Antennas.pdfVIP

Evolutionary Optimization of Yagi-Uda Antennas 1 1 2 Jason D. Lohn , William F. Kraus , Derek S. Linden , and Silvano P. Colombano1 1 Computational Sciences Division, NASA Ames Research Center, Mail Stop 269-1, Moffett Field, CA 94035-1000, USA email: {jlohn, bkraus, colomban }@ 2 Linden Innovation Research, P.O. Box 1601, Ashburn, VA, 20146, USA email: dlinden@ Abstract. Yagi-Uda antennas are known to be difficult to design and optimize due to their sensitivity at high gain, and the inclusion of nu- merous parasitic elements. We present a genetic algorithm-based auto- mated antenna optimization system that uses a fixed Yagi-Uda topology and a byte-encoded antenna representation. The fitness calculation al- lows the implicit relationship between power gain and sidelobe/backlobe loss to emerge naturally, a technique that is less complex than previous approaches. The genetic operators used are also simpler. Our result- s include Yagi-Uda antennas that have excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced via evolutionary algorithms by at least 7.8% in mainlobe gain. We also present encouraging preliminary results where a coevolutionary genetic algorithm is used. 1 Introduction Automated antenna synthesis via evolutionary design has recently garnered much attention in the research literature [12]. Underlying this enthusiasm is an issue that many designers readily acknowledge - good antenna de