The application of global optimization techniques, such as genetic algorithms, to antenna array layouts can provide versatile design methodologies for highly directive, thinned, frequency agile, and shaped-beam antenna systems. However, these methodologies have their limitations when applied to more demanding design scenarios. Global optimizations are not well equipped to handle the large number of parameters used to describe large-N antenna arrays. To overcome this difficulty, a new class of arrays was recently introduced called polyfractal arrays that possess properties well suited for the optimization of large-N arrays. Polyfractal arrays are uniformly excited with an underlying self-similar geometrical structure that leads to aperiodic element layouts. This paper expands on polyfractal array design methodologies by applying a robust Pareto optimization technique with the goal of reducing the peak sidelobe levels at several frequencies specified over a wide bandwidth. A recursive beamforming algorithm and an autopolyploidy based mutation native to polyfractal geometries are used to dramatically accelerate the genetic algorithm optimization process. This paper also demonstrates that the properties of polyfractal arrays can be exploited to create designs that possess no grating lobes and relatively low sidelobe levels over ultrawide bandwidths. The best example discussed in this paper maintains a -15.97 dB peak sidelobe level with no grating lobes from a 0.5λ to more than a 20\lambdaλ minimum spacing between elements, which corresponds to at least a 40:1 bandwidth for the array.
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering