arXiv subjects

Harald Hultin

Publications and source records attributed to Harald Hultin.

3 recordsLinked to original sources

arXiv2026

Investigation of the Asymptotic Properties of Active Impedance in Large Finite Array Antennas

This paper presents an improved full-wave solver for finite array antennas, and uses this solver to examine asymptotic properties of active impedance for large regular arrays. The improved solver is based on a preconditioning scheme that has been adapted for use on more general finite geometries, and an improved data structure. These two improvements result in a fast and stable solver with a lower memory footprint. By investigating the active impedance of finite arrays it is found that, even for arrays with 1000 elements, asymptotic behavior may differ from infinite arrays. Tied to these properties, different predictors on how the active impedance of the center element in the array behaves are presented. The two best predictors work very well for the wideband arrays investigated, and may be used to decide when array approximations, such as unit cell methods, are appropriate, rather than general statements on array size.

physics.comp-ph↗

arXiv2025

Solver Performance of Accelerated MoM for Connected Arrays

Simulating and developing large rectangularly shaped arrays with equidistant interspacing is challenging as the computational complexity grows quickly with array size. However, the geometrical shape of the array, appropriately meshed, leads to a multilevel Toeplitz structure in the RWG-based Method of Moment impedance matrix representation that can be used to mitigate the increased complexity. This paper develops, presents and compares two different accelerated solvers that both utilize the matrix structure to determine antenna properties. Both methods use a novel mesh-partitioning algorithm and its associated data representation, reducing storage and computational costs. The first solver is an iterative method based on multilevel fast Fourier transform to accelerate matrix multiplications. The second solver approach is based on an extension of a fast direct Toeplitz solver, adapted to a block-matrix structure. This fast direct solver is demonstrated to have close to machine epsilon accuracy. Both accelerated methods are evaluated on two different array element types, for arrays with up to 900 elements. The results are compared with conventional direct and iterative matrix solvers. Improvements are seen in both the time and required storage to solve the problem. The choice of the most efficient method depends on the residual thresholds in the iterative method, geometry of the element and frequency. Two different preconditioners for the iterative method are investigated to evaluate their performance. The two accelerated methods vastly outperform regular matrix inversion methods.

math.NA↗

arXiv2025

An Array Decomposition Method for Finite Arrays with Electrically Connected Elements for fast Toeplitz Solvers

A large part of the geometry of array antennas is often partially defined by finite translational symmetries. Applying the method of moments (MoM) with the RWG-like element on an appropriately structured mesh to these arrays results in an impedance matrix where the main part exhibits a multilevel block Toeplitz structure. This article introduces a memory-efficient construction method that effectively represents and reuses impedance calculations. The proposed method, applicable to electrically connected elements, also accounts for all non-symmetric parts of the array. The core idea involves nine distinct electrically connectable components from which the array can be assembled. The derived multilevel block Toeplitz matrix is further utilized by an in-house inverse solver to achieve faster and more memory-efficient MoM current vector calculations. We demonstrate the method by computing the far-field of a 32x32 array and the scattering parameters of two tightly coupled 9x9 arrays. This approach reduces the memory allocation from $\mathcal{O}(N_x^2 N_y^2)$ to $\mathcal{O}(N_x N_y)$, for an $N_x \times N_y$ array.

math.NA↗