Fast Inverse Equivalent Source Solutions With Directive Sources

Eibert, Thomas F.; Vojvodic, Dario; Hansen, Thorkild B.

doi:10.1109/tap.2016.2606405

Cited by 45 publications

(39 citation statements)

References 35 publications

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“…The equivalent surface sources are unknown quantities, which shall be determined in a way that they produce the AUT radiation fields in form of the measurement samples U (r m ) on the measurement surface S, which is in general located in some (arbitrary) distance away from A -typically in the near field of the AUT -and also closed † . Following the notation in [11,22], the probe-weighted radiation integral of the equivalent surface current densities can be written in the form…”

Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

“…Inverse equivalent source configuration with electric and magnetic surface current densities on a Huygens surface A with outward unit normaln and field observations U (r m ) collected on a closed measurement surface S. The infinite volume outside A is called the solution domain and the surface sources on the surface A are equivalent sources representing the radiation fields of all sources within the enclosed AUT volume. chosen as Green's functions of free-space in order to simplify the formulation [11,22,34]. If desired, the formulation can, however, also be extended towards the consideration of other solution environments, such as for measurements above a metallic ground plane [35] or for measurements above a dielectric ground half-space [36,37].…”

Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

“…The formulation of the forward transmission equation from the sources to the measurement probe given in Equation 1is a spatial-domain formulation, which is in this form not very convenient for efficient numerical evaluation. A series of other, spectral formulations based on propagating plane waves, possibly in multi-level representation, or in terms of measured scattering parameters instead of probe voltages, are found in a collection of references, such as [11,[20][21][22]38].…”

Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

“…Instead of working with electric and magnetic surface current densities at the same time, it is also possible to work with just one of these surface current types [5,6,10], where the corresponding integral operators are, however, not advantageous for a solution with an iterative solver. As an approximation of the zero-field condition, the combined-source condition has been proposed in [11] in strong-form, with basis functions in form of the well-known Huygens elementary radiators, and in weak form in [12]. Interesting to mention is also the work described in [13][14][15], where the focus was on radome applications and where the body-of-revolution symmetry was utilized in order to decompose the inverse equivalent current problem by the corresponding eigenmodes.…”

Section: Introductionmentioning

confidence: 99%

“…Very important for large IESSPs is to work with an acceleration approach, which helps to handle the fully-populated matrices resulting from the discretization of the integral operators. Most appropriate appear here approaches following the principles of the fast multipole method (FMM) [23][24][25] or even of the multilevel fast multipole method (MLFMM) [11,20,26,27]. Algebraic compression schemes such as the adpative cross approximation (ACA) method can of course also be employed [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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On the Solution of Inverse Equivalent Surface-Source Problems

Kornprobst¹,

Mauermayer²,

Neitz³

et al. 2019

PIER

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Various formulations of the inverse equivalent surface-source problem and corresponding solution approaches are discussed and investigated. Starting from the radiation integrals of electric and magnetic surface current densities, the probe-corrected inverse equivalent source formulation is set up together with different forms of side constraints such as the zero-field or Love condition. The linear systems of equations resulting from the discretized forms of these equations are solved by the normal residual (NR) and normal error (NE) systems of equations. As expected and as demonstrated by the solution of a variety of inverse equivalent surface-source problems, related to synthetic as well as realistic antenna near-field measurement data, it is found that the iterative solution of the NE equations allows for a better control of the solution error and leads in general to a slightly faster convergence. Moreover, the results show that the incorporation of the zero-field condition into the solution process is in general not beneficial, which is also supported by the structure of the NE systems of equations. If desired, Love surface current densities, or just fields in general, can more easily be computed in a post-processing step. The accuracy of the obtained near-fields and far-fields depends more on the stopping criterion of the inverse source solver than on the particular choice of the equivalent surface-source representation, where the zero-field condition may influence the stopping criterion in a rather unpredictable way.

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Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

Section: Field Transformation Configuration and Basic Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the Solution of Inverse Equivalent Surface-Source Problems

Kornprobst¹,

Mauermayer²,

Neitz³

et al. 2019

PIER

Self Cite

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Mathematical Model for System Planning on Campus: A Case Study in Harbin Institute of Technology in China

Guo

2016

Mediterranean Green Buildings &Amp; Renewable Energy

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The reconstruction of multipolar acoustic or electromagnetic sources from their farfield radiation patterns plays a crucial role in numerous practical applications. Most of the existing techniques for source reconstruction require dense multi-frequency data at the Nyquist sampling rate. Accessibility of only sparse data at a sub-sampled grid contributes to the null space of the inverse source-to-data operator, which causes significant imaging artifacts. For this purpose, additional knowledge about the source or regularization is required. In this article, we propose a novel two-stage strategy for multipolar source reconstruction from the sub-sampled sparse data that takes advantage of the sparsity of the sources in the physical domain. The data at the Nyquist sampling rate is recovered from sub-sampled data and then a conventional inversion algorithm is used to reconstruct sources. The data recovery problem is linked to a spectrum recovery problem for the signal with the finite rate of innovations (FIR) that is solved using an annihilating filter-based structured Hankel matrix completion approach (ALOHA). For an accurate reconstruction of multipolar sources, we employ a Fourier inversion algorithm. The suitability of the suggested approach for both noisy and noise-free measurements is supported by numerical evidence.

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