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Multilevel Fast Multipole Algorithm For Solving Combined Field Integral Equation Of Electromagnetic Scattering

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Abstract

The fast multipole method (FMM) has been implemented to speed up the matrixvector multiply when an iterative method is used to solve combined field integral equation (CFIE). FMM reduces the complexity from O(N 2 ) to O(N 1:5 ). With a multilevel fast multipole algorithm (MLFMA), it is further reduced to O(NlogN ). A 110,592 unknown problem can be solved within 24 hours on a SUN Sparc10. 1. Introduction The electromagnetic (EM) field scattering by three-dimensional (3D) arbitrarily shaped conductor can be obtained by finding the solution of an integral equation where the unknown function is the induced current distribution. The integral equation is discretized into a matrix equation by the method of moments (MOM). The resultant matrix equation y The authors would like to thank L. Hernquist, J.E. Barnes and P. Hut for providing us with copies of their codes, and thank M.B. Woodworth, M.G. Cot'e, and A.D. Yaghjian for providing us with their numerical and experimental data. This wor...
1e-05
0.0001
0.001
0.01
0.1
1
0 50 100 150 200 250 300 350
Normalized Residual Norm
No. of Iterations
r=1m sphere, f=0.72GHz, 294 patches, 9408 unkws
EFIE
MFIE
CFIE
-15
-10
-5
0
5
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Normalized Bistatic RCS (dB)
r=1m sphere, f=0.72GHz, 294 patches, 9,408 unkws
Mie series
EFIE with FMM
MFIE with FMM
CFIE with FMM
θ (Degrees)
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1000 10000 100000
CPU Time Per Iteration (sec)
Unknowns
Without using disk
With using disk
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Memory Requirements (MByte)
Unknowns
Core
Total
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Normalized Bistatic RCS (dB)
θ (Degrees)
r=1m sphere, f=2.4GHz, N=110,592, 6 levels
Mie Series
CFIE with MLFMA
-30
-20
-10
0
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RCS (dBsw)
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2.5 X 2.5 X 3.75 open cavity
LUD
MLFMA
Measurement
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λ
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2.5 X 2.5 X 3.75 λ open cavity
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MLFMA
Measurement
3
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-10
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Bistatic RCS (dBsw)
MLFMA
High Freq.
DMFIE
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Bistatic RCS (dBsw)
MLFMA
High Freq.
DMFIE
k
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θ (Degrees)
... Many real-world electromagnetic (EM) problems require multiscale discretization [1][2][3][4]. When the method of moments (MoM) [5], along with classical fast algorithms, is used to model the multi-scale problems, a single fast algorithm [6][7][8][9][10][11][12] is often insufficient to achieve satisfactory computational performance. Instead, due to capturing both the circuit physics and wave physics [1], hybrid fast algorithms [19][20][21][22] generally provide a more practical path to efficiently solve EM multiscale problems. ...
... As we know, the multilevel fast multipole algorithm (MLFMA) is widely used for efficient simula-tion of electrically large problems [6][7][8]. However, the MLFMA encounters the sub-wavelength breakdown [8] when dense mesh occurs. ...
... Since 1988, he has been with the State Key Laboratory of Millimeter Waves and serves for the director of the lab, since . In 1993, 1995, 1996, and 1998, he was a short-term visiting scholar with the University of California at Berkeley and at Santa Cruz, respectively. He is currently a professor with the School of Information Science and Engineering, Southeast University. ...
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Based on the splitting form of the Green’s function, a hybrid fast algorithm is proposed for efficient analysis of multiscale problems. In this algorithm, the Green’s function is a priori split into two parts: a spectrally band-limited part and a spatially localized part. Then, the fast Fourier transforms (FFT) utilizing the global Cartesian grid and the matrix compression method aided by an adaptive octree grouping are implemented for these two parts, respectively. Compared with the traditional methods which only employ the FFT for acceleration, the proposed hybrid fast algorithm is capable of maintaining low memory consumption in multiscale problems without compromising time cost. Moreover, the proposed algorithm does not need cumbersome geometric treatment to implement the hybridization, and can be established in a concise and straightforward manner. Several numerical examples discretized with multiscale meshes are provided to demonstrate the computational performance of proposed hybrid fast algorithm.
... Over the years, various improvements have emerged to mitigate these restrictions through following different strategies. Notable among these is the Fast Multipole Method (FMM) [2], or its multilevel implementation (MLFMM) [3,4], which facilitates fast matrix−vector product calculations during the iterative solution process and notably reduces memory requirements by storing only the near-field coupling terms. Nonetheless, it is important to note that certain practical challenges may persist, presenting difficult convergences due to either the scale of the problem at hand or the intricate geometric characteristics involved. ...
... Considering how the reduced matrix can be obtained by source-testing block pairs using (3), it becomes apparent that, as previously mentioned, one important computational drawback from the use of large blocks is that we need to compute and store [Z m,k ] in advance. Note that, since the MLFMM is combined with CBFM, the reduced matrix does not need to be complete, and the far-field interactions between CBFs will be considered in the iterative solution process by means of efficient matrix−vector products involving aggregation, translation and disaggregation stages [4]. It is, therefore, only necessary to compute the coupling terms between CBFs located in the same and neighboring blocks. ...
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A technique for the reduction in the CPU-time in the analysis of electromagnetic problems using the Characteristic Basis Function Method (CBFM) is presented here, allowing for analysis of electrically large cases where an iterative solution process cannot be avoided. This technique is based on the use of the Adaptive Cross Approximation (ACA) for the fast computation of the coupling matrix between CBFs belonging to adjacent blocks, as well as the Multilevel Fast Multipole Method (MLFMM) for the computation of matrix−vector products in the solution of the full system. This combination allows for a noticeable reduction in the computational resources during the analysis of electrically large and complex scenarios while maintaining a very good degree of accuracy. A number of test cases serve to validate the presented approach in terms of accuracy, memory and CPU-time compared with conventional techniques.
... The analytical solutions use cylindrical harmonics to expand the fields everywhere in terms of cylindrical harmonics and solve for the expansion coefficients. Traditional numerical methods with the low-order method of moments (MoM) [9], finite element method and finite difference method can also be applied to solve this problem, but are time consuming, although the fast multipole method [10] and multilevel fast multipole algorithm [11] have been applied successfully to accelerate the MoM. The FMM has also been incorprated to accelerate the method of auxiliary sources [12] for a large number of dielectric cylinders. ...
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... Physics of different scales can be isolated into different subdomains, which can be solved locally using methods tailored to their particular features. For example, direct MoM solvers could be used for geometrically intricate but small enough subdomains, while fast iterative solvers like MLFMA [7,8] could be applied for medium to large subdomains. This scheme greatly speeds up convergence in the case of multi-scale problems. ...
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