Application of Pseudoweights in Antenna Array Optimization and Design

A method of selecting an antenna array design from a multiobjective optimization problem is proposed. After locating the Pareto front from a multiobjective problem, multicriterion decision-making (MCDM) can be effectively employed to choose a single design. In this letter, we propose the application of the pseudoweight MCDM method to quickly traverse the efficient set of solutions, providing an efficient approach to designing antenna arrays that match a use case specification. To illustrate this, we consider an automotive radar design operating at 77 GHz. We consider an example tradeoff that seeks to minimize the beamwidth of the antenna mainbeam while also maximizing the peak-to-sidelobe level and directivity. The optimization is completed using the evolutionary algorithm NSGA-II. Finally, the effectiveness of the pseudoweight method in decision-making is demonstrated through a computational speed comparison with another decomposition function, the augmented achievement scalarizing function (AASF). The results show that the pseudoweight method is faster than AASF, promising scalability for quick decision-making in array design problems with many available solutions.