An Efficient Iterative ACA-PO-AWE Method for Broadband Analysis of Platform-Mounted Antennas

This letter proposes a novel hybrid method combining asymptotic waveform estimation (AWE), adaptive cross approximation (ACA), and efficient iterative method of moments–physical optics (efficient iterative MoM-PO) for analyzing wideband radiation characteristics of antennas on large platforms. In the hybrid Efficient Iterative MoM-PO-AWE method, computing self-impedance, mutual-impedance, and their higher-order derivative matrices is essential. However, high-order derivatives lack the block low-rank property, making them unsuitable for direct ACA compression. To address this, we introduce a pseudospectral derivative method-based approach, approximating high-order matrices at the expansion point using zero-order matrices from multiple Gauss–Lobatto–Chebyshev sampling points. By integrating ACA with Efficient Iterative MoM-PO-AWE, the memory usage and computation time have significantly reduced. The method’s accuracy and efficiency are demonstrated through two numerical examples.

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Publication Details

Journal
IEEE Antennas and Wireless Propagation Letters
Published
2025-09-12
DOI
https://doi.org/10.1109/lawp.2025.3609843
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

An Efficient Iterative ACA-PO-AWE Method for Broadband Analysis of Platform-Mounted Antennas

IEEE Antennas and Wireless Propagation Letters
Geochemistry and Geologic Mapping
article

An Efficient Iterative ACA-PO-AWE Method for Broadband Analysis of Platform-Mounted Antennas

article en

Abstract

This letter proposes a novel hybrid method combining asymptotic waveform estimation (AWE), adaptive cross approximation (ACA), and efficient iterative method of moments–physical optics (efficient iterative MoM-PO) for analyzing wideband radiation characteristics of antennas on large platforms. In the hybrid Efficient Iterative MoM-PO-AWE method, computing self-impedance, mutual-impedance, and their higher-order derivative matrices is essential. However, high-order derivatives lack the block low-rank property, making them unsuitable for direct ACA compression. To address this, we introduce a pseudospectral derivative method-based approach, approximating high-order matrices at the expansion point using zero-order matrices from multiple Gauss–Lobatto–Chebyshev sampling points. By integrating ACA with Efficient Iterative MoM-PO-AWE, the memory usage and computation time have significantly reduced. The method’s accuracy and efficiency are demonstrated through two numerical examples.

IEEE Antennas and Wireless Propagation LettersVol. 24(12)
Xidian University (CN)
Affordable and clean energy
Openalex Percentile: Top 37%
Geochemistry and Geologic Mapping
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