scholarly journals Broadband Adaptive RCS Computation through Characteristic Basis Function Method

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Guohua Wang ◽  
Yufa Sun
Keyword(s):  
Cross Section ◽  
Basis Function ◽  
Function Method ◽  
High Accuracy ◽  
Wide Frequency Range ◽  
Singular Value ◽  
Basis Functions ◽  
Frequency Range ◽  
Arbitrary Frequency ◽  
Value Decomposition

A broadband radar cross section (RCS) calculation approach is proposed based on the characteristic basis function method (CBFM). In the proposed approach, the desired arbitrary frequency band is adaptively divided into multiple subband in consideration of the characteristic basis functions (CBFs) number, which can reduce the universal characteristic basis functions (UCBFs) numbers after singular value decomposition (SVD) procedure at lower subfrequency band. Then, the desired RCS data can be obtained by splicing the RCS data in each subfrequency band. Numerical results demonstrate that the proposed method achieve a high accuracy and efficiency over a wide frequency range.

Ultra-wideband characteristic basis function method merging the secondary level characteristic basis functions for rapid computation of wideband radar cross section problems from conducting targets

2020 ◽  
pp. 1-10
Author(s):  
Zhong-Gen Wang ◽  
Jun-Wen Mu ◽  
Wen-Yan Nie
Keyword(s):  
Basis Function ◽  
Function Method ◽  
Secondary Level ◽  
Singular Value ◽  
Basis Functions ◽  
Ultra Wideband ◽  
Scattering Problems ◽  
Wideband Radar ◽  
Value Decomposition ◽  
A Current

In this paper, a merged ultra-wideband characteristic basis function method (MUCBFM) is presented for high-precision analysis of wideband scattering problems. Unlike existing singular value decomposition (SVD) enhanced improved ultra-wideband characteristic basis function method (SVD-IUCBFM), the MUCBFM reduces the number of characteristic basis functions (CBFs) necessary to express a current distribution. This reduction is achieved by combining primary CBFs (PCBFs) with the secondary level CBFs (SCBFs) to form a single merged ultra-wideband characteristic basis function (MUCBF). As the MUCBF incorporates the effects of PCBFs and SCBFs, the accuracy does not change significantly compared to that obtained by the SVD-IUCBFM. Furthermore, the efficiencies of constructing the CBFs and filling the reduced matrix are improved. Numerical examples verify and demonstrate that the proposed method is credible both in terms of accuracy and efficiency.

scholarly journals Efficient Computation of Wideband RCS Using Singular Value Decomposition Enhanced Improved Ultrawideband Characteristic Basis Function Method

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Wen-yan Nie ◽  
Zhong-gen Wang
Keyword(s):  
Singular Value Decomposition ◽  
Basis Function ◽  
Matrix Equation ◽  
Function Method ◽  
Plane Waves ◽  
Singular Value ◽  
Efficient Computation ◽  
Incident Plane ◽  
Filling Time ◽  
Value Decomposition

The singular value decomposition (SVD) enhanced improved ultrawideband characteristic basis function method (IUCBFM) is proposed to efficiently analyze the wideband scattering problems. In the conventional IUCBFM, the SVD is only applied to reduce the linear dependency among the characteristic basis functions (CBFs) due to the overestimation of incident plane waves. However, the increase in the size of the targets under analysis will require a large number of incident plane waves and it will become very time-consuming to solve such numbers of the matrix equation. In this paper, the excitation matrix is compressed by using the SVD in order to reduce both the number of matrix equation solutions and the number of CBFs compared with the traditional IUCBFM. Furthermore, the dimensions of the reduced matrix and the reduced matrix filling time are significantly reduced. Numerical results demonstrate that the proposed method is accurate and efficient.

Evaluating EM waveforms by singular‐value decomposition of exponential basis functions

Geophysics ◽  
1998 ◽  
Vol 63 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Edward M. Stolz ◽  
James Macnae
Keyword(s):  
Singular Value Decomposition ◽  
Pulse Length ◽  
Singular Value ◽  
Basis Functions ◽  
Step Response ◽  
Waveform Data ◽  
Time Constants ◽  
Exponential Basis ◽  
Response Systems ◽  
Value Decomposition

Exponential basis functions preconvolved with the system waveform are used to convert measured transient decays to an ideal frequency‐domain response that can be modeled more easily than arbitrary waveform data. Singular‐value decomposition (SVD) of the basis functions are used to assess which specific EM waveform provides superior resolution of a range of exponential time constants that can be related to earth conductivities. The pulse shape, pulse length, transient sampling scheme, noise levels, and primary field removal used in practical EM systems all affect the resolution of time constants. Step response systems are more diagnostic of long time constants, and hence good conductors, than impulse response systems. The limited bandwidth of airborne EM systems compared with ground systems is improved when the response is sampled during the transmitter on time and gives better resolution of short time constants or fast decays.

scholarly journals CONTINUATION FOR NONLINEAR ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS DISCRETIZED BY THE MULTIQUADRIC METHOD

2000 ◽  
Vol 10 (02) ◽  
pp. 481-492 ◽  
Author(s):  
A. I. FEDOSEYEV ◽  
M. J. FRIEDMAN ◽  
E. J. KANSA
Keyword(s):  
Basis Function ◽  
Elliptic Partial Differential Equations ◽  
High Accuracy ◽  
Basis Functions ◽  
Elliptic Pdes ◽  
Algebraic Equations ◽  
Nonlinear Elliptic ◽  
Interpolation Problems ◽  
Nonlinear Algebraic Equations ◽  
Meshless Collocation

The Multiquadric Radial Basis Function (MQ) Method is a meshless collocation method with global basis functions. It is known to have exponentional convergence for interpolation problems. We descretize nonlinear elliptic PDEs by the MQ method. This results in modest-size systems of nonlinear algebraic equations which can be efficiently continued by standard continuation software such as AUTO and CONTENT. Examples are given of detection of bifurcations in 1D and 2D PDEs. These examples show high accuracy with small number of unknowns, as compared with known results from the literature.

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