AI & ML
A Manifold-Based Framework for Coupling-Aware Surrogate Optimization of Antenna Arrays Using Characteristic Modes
arXiv eess.SP0 views
arXiv:2605.23851v2 Announce Type: replace Abstract: A surrogate-based synthesis framework for antenna arrays is presented that incorporates mutual coupling while keeping optimization computationally efficient. The method combines a common characteristic-mode basis, a global modal coupling model, and element-wise generalized scattering matrices (GSMs). Array design variables are formulated and optimized on physically meaningful manifolds, in particular the manifold of unitary symmetric matrices for reciprocal and lossless element GSMs. A staged penalty strategy is used to progressively enforce sidelobe and cross-polarization constraints during multi-beam optimization. The framework is demonstrated for an $8\times8$ left-handed circularly polarized patch phased array with scan behavior in one principal plane. Different degree-of-freedom assignment strategies are compared, showing that constrained non-identical element classes can satisfy stringent pattern requirements where equal-element designs fail. For the demonstrated case, the optimization converges within seconds on a single CPU core, and full-wave verification of the realized arrays confirms the predicted trends, with good agreement for the SLL and useful accuracy for the XPR. The results indicate that the proposed formulation is a practical and scalable route for coupling-aware array synthesis and realization.
Source:https://arxiv.org/abs/2605.23851PreviousUAV Energy Consumption Models for Wireless Systems Research: Model Selection and MisconceptionsNextOptimizing GEDI Simulator Configuration for European Temperate Forests
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