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The aim of this article is to perform a rapid electromagnetic (EM) analysis of large perfectly electric conducting (PEC) platforms with local variations. Such problems often require many-query simulations to navigate complex parameter spaces and thus quickly become computationally expensive. The proposed work starts with a stationary-variable domain decomposition, where the computational domain is decomposed into large fixed parts and small portions with local variations. Subsequently, we introduce a separable and compressible platform Green’s function at the outer surface of those variable subdomains in an upfront offline calculation. Once obtained, the online computational complexity does not depend on the size of the in situ platform. With the validation of numerical results, we conclude that the proposed work has the potential to greatly speed up the online evaluation of local designs and optimizations compared to the brute-force computation. [ABSTRACT FROM AUTHOR]

This communication provides a novel adaptive irregular grid model (AIGM) to improve the scattering simulation efficiency of electrically large terrains. This model distinguishes the steep and flat regions of the measured topographic point cloud models by a threshold. To determine the optimal threshold, we present the height gradient as the criterion to describe the topographic undulation. The optimal threshold is located at the inflection point of the curve describing topographic similarity in the range of height gradient. This generated AIGM can reduce the grid quantity and maintain consistency with the original point cloud model. It is also valuable in the popular coherent and incoherent (C&I) scattering model of global navigation satellite system reflectometry (GNSS-R). In this communication, the coherent component can be expressed by a simple product of the electric field of the conductor grid, the characteristic function of roughness, and the Fresnel reflection coefficient. The incoherent component comes from the diffuse scattering simulated by the integral equation method (IEM). Compared with the traditional solution to C&I scattering by using the Kirchhoff approximation (KA), the modified C&I model has a more extensive application. The precision of the AIGM-based-C&I model is verified by traditional physical optics (PO). The excellent simulation efficiency of the AIGM-based-C&I model is also demonstrated. [ABSTRACT FROM AUTHOR]

A flexible and efficient resistive sheet boundary condition (RSBC)-based hybrid finite element-boundary integral-multilevel fast multipole algorithm (FE-BI-MLFMA) is presented for computing electromagnetic scattering from inhomogeneous objects with microwave-absorbing honeycomb structures. In the proposed algorithm, each nonmagnetic and high lossy material coated unit cell wall of the honeycomb is first approximated by the multilayered RSBC as a zero-thickness resistive sheet to eliminate the computational burden due to the extremely thin and multilayered characteristics of the coated unit cell wall. Then, the RSBC is incorporated into the FE-part of the FE-BI-MLFMA formulation. To further reduce the burden of meshing complicated objects involving cellular structures after RSBC approximation, the hybrid conformal and nonconformal domain decomposition method (DDM) of the FE-BI-MLFMA, which integrates the nonconformal Schwarz DDM-FE and the simplified discontinuous Galerkin (S-DG), is employed to bring significant flexibility and versatility in geometry modeling and mesh generating. An effective block low-rank multifrontal solver-based domain decomposition finite-element method (FEM)-absorbing boundary condition (ABC) preconditioner is constructed to speed up the solution of the FE-BI equations using locally approximated integral operators for the BI part. Numerical examples are given to demonstrate the accuracy, capability, and performance of the proposed algorithm, including a high-definition complicated fighter model with antenna array, multilayer dielectric radome, and microwave-absorbing honeycomb structures. [ABSTRACT FROM AUTHOR]

We present a surface integral equation (SIE) solution for a special class of anisotropic media, whose permittivity and permeability are both symmetric full tensors with the same or multiple values. This kind of media is generated from the invisible cloaking or absorbing material of a perfectly matched layer (PML) design. A new derivation based on the potential functions is presented to obtain the closed-form Green’s function. Detailed and rigorous proofs of some vector identities are given for the first time. Special treatments are detailed to address the singularity of the anisotropic Green’s function for discretizing the SIE. Numerical experiments validate the accuracy, stability, and high efficiency of the proposed solution compared with the analytical solution or the finite element-boundary integral (FE-BI) method. [ABSTRACT FROM AUTHOR]

In this communication, we combine the facet-based bidirectional reflection distribution function (BRDF) and four-path model (FPM) to establish the attribute scattering center (ASC) model for composite scattering simulations. This hybrid method is beneficial for simulating scattering echoes of large composite scenes with high efficiency. The model consists of three parts: the ASC model for the target, the BRDF-ASC model for the rough dielectric background, and the FPM-BRDF-ASC model for the coupling scattering between the target and the background. Two simple composite scenes and two large composite scenes are taken as examples to verify the accuracy and feasibility of the proposed model. The validation results show that the radar cross sections (RCSs) of the proposed hybrid method are consistent with those of the multilevel fast multipole algorithm (MLFMA) with higher simulation efficiency. In addition, the ghosting image caused by the multipath effect can be well displayed in the simulated synthetic aperture radar (SAR) images. [ABSTRACT FROM AUTHOR]

In this article, a massively parallel approach of the multilevel fast multipole algorithm (PMLFMA) on graphics processing unit (GPU) heterogeneous platform, noted as GPU-PMLFMA, is presented for solving extremely large electromagnetic scattering problems involving tens of billions of unknowns, In this approach, the flexible and efficient ternary partitioning scheme is employed at first to partition the MLFMA octree among message-passing interface (MPI) processes. Then, the computationally intensive parts of the PMLFMA on each MPI process, matrix filling, aggregation and disaggregation, and so on are accelerated by using the GPU. Different parallelization strategies in coincidence with the ternary parallel MLFMA approach are designed for GPU to ensure high computational throughput. Special memory usage strategy is designed to improve computational efficiency and benefit data reusing. The CPU/GPU asynchronous computing pattern is designed with the OpenMP and compute unified device architecture (CUDA), respectively, for accelerating the CPU and GPU execution parts and computation time overlapped. GPU architecture-based optimization strategies are implemented to further improve the computational efficiency. Numerical results demonstrate that the proposed GPU-PMLFMA can achieve over three times speedup, compared with the eight-threaded conventional PMLFMA. Solutions of scattering by electrically large and complicated objects with about 24 000 wavelengths and over 41.8 billion unknowns are presented. [ABSTRACT FROM AUTHOR]

The mechanism of each term in the discontinuous Galerkin (DG) method is analyzed and studied numerically. A simplified DG self-dual integral equation (SDIE) formulation is proposed for solving electromagnetic scattering from large-scale objects with impedance boundary condition (IBC). Numerical results show that the proposed formulation is more flexible and memory saving than the conventional DG formulations, especially for implementing the multilevel fast multipole algorithm (MLFMA). Moreover, a massively parallel strategy of the MLFMA is employed to further strengthen its capability for electrically large problems. Numerical experiments demonstrate the accuracy and efficiency of the proposed formulation for analyzing electromagnetic scattering problems of IBC objects with billions of unknowns. [ABSTRACT FROM AUTHOR]

We present in this letter an efficient numerical method for the analysis of electromagnetic scattering by inhomogeneous objects with arbitrarily oriented honeycomb radar absorbing structures. In this method, each cellular honeycomb structure is first homogenized as a diagonal anisotropic medium in local coordinate system by using a new hybrid Hashin–Shtrikman and Mori–Tanaka formula. Then, a Euler rotation matrix is employed for describing a honeycomb structure with arbitrary orientation in a global coordinate system by transforming a diagonal tensor into a general 3 × 3 tensor. Finally, the object with homogenized honeycomb structures are simulated by using the nonconformal domain decomposition finite element-boundary integral-multilevel fast multipole algorithm. Numerical examples are presented to demonstrate the accuracy, efficiency and capability of the proposed algorithm, including the scattering by a typical sandwich panel with honeycomb core, and a complicated fighter model which includes antenna array, dielectric radome and radar-absorbing honeycomb structure. [ABSTRACT FROM AUTHOR]

Radar imaging of typical planet landforms can be used for planetary exploration such as landform recognition and geometry measurement. This communication realizes high-resolution imaging simulations of typical planetary landforms, such as craters, hills, and volcanoes, by using parametric scattering center (SC) models. Based on the geometric models of these typical landforms, parametric SC models are constructed from scattered solutions of the physical optics (POs) method. Because the SC models take geometric parameters as model parameters, these models can simulate the scattered waves of landforms of different sizes. These SC models are validated by the PO results. In addition, the landform types can be recognized and their geometrical parameters are further extracted by SC model matching. The extracted geometric parameters show good agreement with real landforms, demonstrating that the SC models of typical planetary landforms have potential applications in planetary geomorphologic exploration. [ABSTRACT FROM AUTHOR]

The phase information's role in deep neural networks (DNNs) to solve the electromagnetic inverse scattering problems is investigated. The feedforward neutral network model with complex-valued (CV) data stream and the corresponding CV backpropagation training algorithm are proposed to realize CV convolutional neural networks. Numerical examples are carried out to demonstrate the phase information's role in DNNs in terms of generalization capability as well as the convergence speed in the training stage. [ABSTRACT FROM AUTHOR]

Our numerical experiments show that the hierarchical matrix (H-matrix) solver is more efficient than the butterfly solver for electrically small problems, although the converse is true for sufficiently large problems. In this communication, we propose a hybrid matrix decomposition algorithm (HMDA) that combines the H-matrix and butterfly algorithms. In the HMDA, the H-matrix algorithm is employed to compress the lower–upper decomposition matrix in the lower levels, whereas the butterfly algorithm is adopted at the higher levels. Numerical examples demonstrate that the performance of the HMDA is similar to that of the H-matrix for electrically small problems and higher than the butterfly algorithm for electrically large problems. [ABSTRACT FROM AUTHOR]

In this communication, we present flexible and efficient solutions of large-scale electromagnetic scattering problems using the parallel discontinuous Galerkin (DG) surface integral equation (SIE) method. A simplified formulation of the conventional DG is used by removing the interior penalty term, thereby avoiding computational burden of the contour integral in the conventional DG. It is demonstrated numerically that the simplification causes convergence deficiency and changes the accuracy convergence rate of the solution for objects with sharp corners. The former is overcome by constructing preconditioners using the near-field matrix of the whole region, and the latter is proved to have a neglectable influence on the accuracy of the final solutions as long as normal mesh density requirement is satisfied. The wellscaling ternary parallelization approach of the multilevel fast multipole algorithm (MLFMA) is incorporated into the DG domain decomposition framework to reduce the complexity of the solution and strength its capability for large-scale problems, with the distribution of the nearfield-related calculation adjusted to adapt the nonuniform meshes for a better workload balance. Numerical results are included to validate the accuracy and demonstrate the scalability and versatility of the proposed method. In addition, we demonstrated the effectiveness of our algorithm by solving a high-definition complicated aircraft model with inlets and exhausts involving over one billion unknowns. [ABSTRACT FROM AUTHOR]