Adaptive Multi-Taper High-Order Spectral-Domain Framework for Efficient Modeling and Analysis of Synthetic Aperture Antennas

Efficient electromagnetic modeling of synthetic aperture antennas (SAAs) remains challenging for electrically large or irregularly sampled apertures, where conventional full-wave solvers are computationally expensive. This paper proposes an Adaptive Multi-Taper High-Order Spectral-Domain (AMT-SD) method that combines high-order spectral representations with discrete prolate spheroidal sequence (DPSS)-based multi-taper estimation to reduce spectral leakage and improve robustness under noise and nonuniform sampling. Numerical results for rectangular and circular apertures show that AMT-SD achieves accuracy comparable to direct numerical integration (DNI) while offering improved stability and significantly reduced computational cost. The use of low-rank kernel compression further enhances scalability for large-scale problems. These results demonstrate that AMT-SD provides an effective balance between accuracy, stability, and efficiency for synthetic aperture antenna analysis.