A Novel Hybrid Algorithm for Source Reconstruction Method in Near-Field Prediction

Abstract

Advanced packaging in electronic systems presents new challenges for electromagnetic interference issues. The source reconstruction method (SRM) based on near-field scanning provides a solution for locating electromagnetic interference sources and reconstructing the electromagnetic field inside the package. The traditional SRM based on least squares methods relies on phase information, leading to expensive measurement facilities and complex testing processes. As a result, phaseless SRMs with lower testing requirements have become a research hotspot. However, these methods require solving a nonlinear equation, which lacks an explicit solution and poses difficulties in extracting the equivalent radiation source. To address this issue, a new phaseless SRM that achieves high precision and efficiency is proposed. The method combines the advantages of the differential evolution (DE) algorithm with the covariance matrix adaptation evolution strategy (CMA-ES) algorithm, offering fast convergence speed and high accuracy. Compared to the conventional DE algorithm, the proposed hybrid method reduces the error of the reconstructed field by an average of 9% and improves the accuracy of the predicted field from 82% to 85% while accelerating convergence.