학술논문

Numerical Results on the Use of the L-SVD Approach for the Solution of the Inverse Source Problem from Amplitude-Only Data
Document Type
Conference
Source
2024 18th European Conference on Antennas and Propagation (EuCAP) Antennas and Propagation (EuCAP), 2024 18th European Conference on. :1-4 Mar, 2024
Subject
Fields, Waves and Electromagnetics
Training
Fourier transforms
Inverse problems
Neural networks
Europe
Current distribution
Electromagnetics
Inverse source
amplitude-only
L-SVD
TSVD
Deep Neural Networks
Language
Abstract
We consider a Learned Singular Value Decomposition (L-SVD) approach to face a canonical 2D scalar inverse source problem from amplitude-only, far-field data. We compare the reconstruction performance of L-SVD from amplitude-only data against the Truncated SVD (TSVD) regularized inversion using amplitude and phase (complex) information. The numerical tests show that phaseless L-SVD provides, with a proper training on a well-organized dataset accommodating significant a priori information on the set of relevant unknown current distributions, superior performance as compared to TSVD.