【摘要】：高效矩量法(MoM)適合于電大尺寸目標(biāo)電磁散射特性的計(jì)算分析。本文以矩量法分析金屬介質(zhì)復(fù)合目標(biāo)的電磁散射特性為背景,以自適應(yīng)交叉近似算法(ACA)和特征基函數(shù)法(CBFM)等高效數(shù)值算法為基礎(chǔ),在多角度單站散射、寬頻帶單站散射的快速分析方法以及迭代求解的加速方法上進(jìn)行進(jìn)一步的研究。主要研究工作如下:1.利用快速自適應(yīng)交叉近似(FACA)算法加速目標(biāo)多角度散射特性的分析。通過(guò)FACA算法對(duì)多角度入射平面波形成的激勵(lì)矩陣進(jìn)行分解、壓縮并表示成三個(gè)矩陣相乘的分解式,再利用該分解式改變了需要求解的矩陣方程形式,從而有效減少了MoM矩陣方程求解的次數(shù),降低了總計(jì)算復(fù)雜度。2.基于寬帶特征基函數(shù)(UCBFs),利用縮減阻抗矩陣插值技術(shù)加速目標(biāo)的寬頻帶單站RCS的計(jì)算�；谛〔ㄌ匦�,特征基函數(shù)被拓展為寬帶特征基函數(shù),并用于生成采樣頻率點(diǎn)的縮減阻抗矩陣。縮減阻抗矩陣插值技術(shù)通過(guò)插值方法直接獲取每個(gè)分析頻點(diǎn)下的縮減阻抗矩陣,提升了矩陣填充效率,進(jìn)一步減少了計(jì)算時(shí)間。3.利用自適應(yīng)采樣技術(shù)優(yōu)化的稀疏化自適應(yīng)交叉近似(SPACA)算法及其與特征基函數(shù)法(CBFM)的混合方法加速M(fèi)oM矩陣方程的迭代求解。在各種低秩分解算法中,SPACA在50?以內(nèi)的導(dǎo)體目標(biāo)的RCS計(jì)算中優(yōu)勢(shì)明顯,本文將其拓展到分析金屬介質(zhì)復(fù)合目標(biāo)的電磁散射特性計(jì)算中;針對(duì)其不足,進(jìn)一步引入CBFM,有效縮減了迭代求解方法所占用的內(nèi)存和計(jì)算時(shí)間。
[Abstract]:The high efficient moment method (MoM) is suitable for the calculation and analysis of electromagnetic scattering characteristics of electrically large size targets. In this paper, based on the analysis of electromagnetic scattering characteristics of metal dielectric composite targets by the method of moments, and based on the high efficiency numerical algorithms such as adaptive cross approximation algorithm (ACA) and eigenbase function method (CBFM), the scattering is carried out in single station at multiple angles. The fast analysis method of wide-band monostatic scattering and the acceleration method of iterative solution are further studied. The main research work is as follows: 1. The fast adaptive cross approximation (FACA) algorithm is used to accelerate the analysis of multi-angle scattering. The excitation matrix formed by multi-angle incident plane wave is decomposed by FACA algorithm, which is compressed and expressed as a factorization of three matrices multiplying. The matrix equation that needs to be solved is changed by using the decomposition formula. Thus, the number of MoM matrix equations is reduced effectively, and the total computational complexity is reduced. 2. 2. Based on the wideband feature basis function (UCBFs), the reduced impedance matrix interpolation technique is used to accelerate the calculation of the wide-band mono-static RCS of the target. Based on the wavelet characteristics, the feature basis function is extended to the wideband feature basis function and used to generate the reduced impedance matrix of sampling frequency points. The reduced impedance matrix interpolation technique directly acquires the reduced impedance matrix at each analysis frequency by interpolation method, which improves the filling efficiency of the matrix and further reduces the calculation time. The sparse adaptive crossover approximation (SPACA) algorithm optimized by adaptive sampling technique and its hybrid method with the eigenbase function method (CBFM) are used to accelerate the iterative solution of MoM matrix equation. In all kinds of low rank decomposition algorithms, SPACA is in the range of 50? In this paper, the RCS calculation of the conductor target is extended to the analysis of the electromagnetic scattering characteristics of the metal dielectric composite target. In order to solve this problem, CBFM, is introduced to reduce the memory and computing time.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O441;O241.6

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本文編號(hào)：2364574