Multi-Objective System-by-Design for mm-Wave Automotive Radar Antennas

TL;DR

This paper introduces a novel System-by-Design method that efficiently solves multi-objective optimization problems for designing mm-wave automotive radar antennas, combining evolutionary algorithms with AI/ML for high computational efficiency.

Contribution

A new MO-SbD approach is developed, integrating evolutionary concepts with AI/ML to optimize electromagnetic device design with reduced computational time.

Findings

High computational efficiency demonstrated

Significant time savings over existing methods

Effective in designing mm-wave automotive radar antennas

Abstract

The computationally-efficient solution of multi-objective optimization problems (MOPs) arising in the design of modern electromagnetic (EM) microwave devices is addressed. Towards this end, a novel System-by-Design (SbD) method is developed to effectively explore the solution space and to provide the decision maker with a set of optimal trade-off solutions minimizing multiple and (generally) contrasting objectives. The proposed MO-SbD method proves a high computational efficiency, with a remarkable time saving with respect to a competitive state-of-the-art MOP solution strategy, thanks to the "smart" integration of evolutionary-inspired concepts and operators with artificial intelligence (AI) and machine learning (ML) techniques. Representative numerical results are reported to provide the interested users with useful insights and guidelines on the proposed optimization method as well as to assess its effectiveness in designing mm-wave automotive radar antennas.