Application of Pseudoweights in Antenna Array Optimization and Design

A method of selecting an antenna array design from a multi-objective optimization problem is proposed. After locating the Pareto front from a multi-objective problem, multi-criterion decision-making (MCDM) can be effectively employed to choose a single design. In this letter, we propose the application of the pseudo-weight 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 trade-off that seeks to minimize the beamwidth of the antenna mainbeam while also maximizing the peak-to-sidelobe level (SLL) and directivity. The optimization is completed using the evolutionary algorithm NSGA-II. Finally, the effectiveness of the pseudo-weight 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 pseudo-weight method is faster than AASF, promising scalability for quick decision-making in array design problems with many available solutions.