Characteristic Mode Analysis of Large-Scale Finite Array Structures Above a Half-Space
Abstract
This article presents an efficient half-space characteristic mode analysis (HSCMA) framework for the accurate analysis of large-scale finite periodic structures above a half-space. Finite periodic structures above a half-space are commonly analyzed using either the half-space periodic Green’s function method or the half-space integral equation method. The former models a finite array through the infinite array approximation and provides acceptable accuracy only for sufficiently large arrays with uniformly spaced elements but generally fails to capture edge effects accurately. The latter provides a rigorous full-wave solution, but is computationally prohibitive for electrically large structures because of the large number of unknowns and the associated dense impedance matrix. To overcome this limitation and improve modeling accuracy, characteristic modes (CMs) of an element in the half-space finite periodic structure are extracted. The extracted CMs are then employed as entire-domain basis functions to reduce the order of the discretized impedance matrix. To further accelerate matrix filling, matrix reuse and list interpolation techniques are applied. Moreover, the multilevel fast multipole algorithm (MLFMA) is integrated into the HSCMA framework to expedite matrix-vector multiplication during the solution of electromagnetic scattering problems involving electrically large finite periodic structures above a half-space. The improved accuracy and efficiency of the method are validated through numerical examples. Compared with commercial software, the proposed approach achieves a 94% reduction in computational time and a 69% decrease in memory usage.
Fields of Study & Subjects
Antenna Design and Optimization
Acoustic Wave Phenomena Research
Electromagnetic Scattering and Analysis
Publication details
- Journal / source
- IEEE Transactions on Microwave Theory and Techniques
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 74
- Issue
- 7
- Pages
- 5974–5986
- Publication date
- 12 May 2026