An Enhanced Bayesian Compressive Sensing Method of Moments for Monostatic Scattering Problems

Authors

  • Longhui Sun School of Electrical and Information Engineering Anhui University of Science and Technology, Huainan 232001, China
  • Zhonggen Wang School of Electrical and Information Engineering Anhui University of Science and Technology, Huainan 232001, China
  • Chenlu Li School Electrical and Information Engineering Hefei Normal University, Hefei 230061, China

DOI:

https://doi.org/10.13052/2025.ACES.J.401203

Keywords:

Bayesian compressive sensing, method of moments, monostatic scattering problems

Abstract

In this paper, an Enhanced Bayesian Compressive Sensing method based on the Method of Moments (EBCS-MoM) is proposed to accelerate the solution of three-dimensional electromagnetic scattering problems. Unlike conventional Bayesian Compressive Sensing method based on the Method of Moments (BCS-MoM) approaches, EBCS-MoM employs a Gaussian Scale Mixture prior to model parameters and introduces Laplace or Student’s T hyperpriors to induce sparsity. To reduce the high computational cost of matrix inversion in traditional BCS-MoM, EBCS-MoM uses a surrogate function to approximate the Gaussian likelihood, allowing for an analytical posterior form. The algorithm then maximizes the marginal likelihood to construct a joint optimization problem, which is efficiently solved under the Majorization–Minimization framework using a Block Coordinate Descent method. This reduces the per-iteration complexity to o(n2). Numerical results demonstrate that the proposed method significantly accelerates computation while maintaining accuracy.

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Author Biographies

Longhui Sun, School of Electrical and Information Engineering Anhui University of Science and Technology, Huainan 232001, China

Longhui Sun received the B.E. degree from Fuyang Normal University, China, in 2022. He is currently pursuing the M.S degree at Anhui University of Science and Technology. His current research interest lies in the application of Bayesian compressive sensing in electromagnetic scattering.

Zhonggen Wang, School of Electrical and Information Engineering Anhui University of Science and Technology, Huainan 232001, China

Zhonggen Wang received the Ph.D. degree in electromagnetic field and microwave technique from the Anhui University of China (AHU), Hefei, P. R. China, in 2014. Since 2014, he has been with the School of Electrical and Information Engineering, Anhui University of Science and Technology. His research interests include computational electromagnetics, array antennas, and reflect arrays.

Chenlu Li, School Electrical and Information Engineering Hefei Normal University, Hefei 230061, China

Chenlu Li received the Ph.D. degree from Anhui University, China, in 2017. She is currently working at Hefei Normal University. Her research interests electromagnetic scattering analysis of targets and filtering antenna design.

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Published

2025-12-30

How to Cite

[1]
L. . Sun, Z. . Wang, and C. . Li, “An Enhanced Bayesian Compressive Sensing Method of Moments for Monostatic Scattering Problems”, ACES Journal, vol. 40, no. 12, pp. 1160–1168, Dec. 2025.

Issue

2025: Vol 40 Iss 12

Section

General Submission

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