Multiobjective Optimization Design Of Two-Folded Yagi Antenna Using Niched Genetic Algorithms

With the development of invisible aircrafts and anti-radar missiles, meter-wave radar, which played an important role in the history of radar, has been focused on once again. Since the RCS of invisible aircrafts is very small, general radar finds it difficult to catch them. Comparatively speaking, meter-wave radars working at 300MHz below has advantages in searching out invisible objectives and avoiding ARM. Hence, more and more countries are paying attention to the modification of meter-wave radars in service and the development of next generation meter-wave radars.In order to develop a miniature meter-wave Yagi radar, work has been done by multi-objective optimizing a novel compact Yagi antenna, two-folded Yagi antenna, using niched genetic algorithms.Based on the relationship between element spacing and directivity, input impedance, radiation efficiency and model simulation, a folded structure is taken to form closely spaced Yagi, which has proved to reduce the boom length without impedance dismatch and low efficiency.Genetic algorithms are introduced to optimize two-folded Yagi antenna because there are many configuration parameters and serious coupling phenomena in folded structure Yagi. Considering the multi-objective optimization of antennas, we take niched genetic algorithms into the synthesis process. It is concluded that a three-element two-folded Yagi antenna at 100MHz-300MHz can achieve a realized gain of 7.6dB, 0.45dB higher than a conventional Yagi, and the boom length is only 0.05λ, decreasing by 4 times of a conventional one. A four-element two-folded Yagi antenna at 300MHz can achieve a realized gain of 9.54dB, nealy the same as a conventional Yagi, while the boom length is about 0.3λ, two-third of a conventional one.