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復合目標電磁散射高頻方法研究

發(fā)布時間:2018-12-17 18:43
【摘要】:近年來與隨機粗糙面相關的應用越來越多,因此與它相關的電磁散射特性問題的研究受到了大量研究人員廣泛而全面的關注,特別是關于它與三維散射體構成的復合目標的雷達散射截面(RCS)的計算更是成為了電磁計算領域中的重點、難點和熱點問題,對人們的日常生產(chǎn)生活有著舉足輕重的作用和巨大的影響。但是由于復合目標通常比較復雜,要對其進行仿真計算,需要對算法的適用范圍、計算效率和內(nèi)存消耗等提出很嚴苛的要求,而現(xiàn)有的多數(shù)算法都受限于自身的適用范圍和計算效率不能有效地計算復合目標的散射問題。鑒于彈跳射線法(Shooting and Bounce Rays)具有使用范圍廣、計算效率高并且能求解出具有較高精度結果等優(yōu)點,因此本文采用SBR來求解復合目標的電磁散射特性問題。本文的研究工作如下:1.本文首先對研究隨機粗糙面電磁散射問題的歷史進行了回顧并對相應的計算方法進行了介紹,總結出了它們的應用范圍和優(yōu)缺點。并結合隨機粗糙面自身具有的各種特征和屬性,因此決定將SBR作為本文對其電磁散射問題研究的重點內(nèi)容;2.由于復合目標的外形特征較為復雜,當用平面三角面元對其離散時,會丟失掉全部的關于表面的曲率信息,從而使SBR的計算精度下降,以至于在求解包含有凹面結構的散射體時會給出錯誤的結果。對此本文引進了虛擬發(fā)散因子(Virtual Divergence Factor,VDF),可以修正曲率信息的丟失,從而保證了SBR的計算精度。同時又由于復合目標往往為電大尺寸目標,因而用來離散其的三角面元數(shù)目較多,因此本文又引進了Kd-tree數(shù)據(jù)結構traverse,ART)法來加速對Kd-tree的遍歷,從而大大提高了SBR的計算效率;3.用改進后的SBR計算大量典型目標的雷達散射截面(RCS),該結果與數(shù)值方法求解的結果和測量結果吻合的很好,充分證明了SBR具有廣泛的使用范圍、卓越的計算效率和良好的計算精度。最后本文成功將該方法用于隨機海面分別與導彈和艦船組成的復合目標RCS的仿真計算。
[Abstract]:In recent years, there are more and more applications related to random rough surfaces, so the study of electromagnetic scattering characteristics related to random rough surfaces has attracted extensive and comprehensive attention of a large number of researchers. In particular, the calculation of radar cross section (RCS) of a composite target composed of three dimensional scattering objects has become an important, difficult and hot issue in the field of electromagnetic calculation. It plays an important role in people's daily production and life. However, due to the complexity of complex targets, it is necessary to make strict demands on the application range, computational efficiency and memory consumption of the algorithm in order to simulate it. However, most of the existing algorithms are limited by their scope of application and computational efficiency can not effectively calculate the scattering problem of composite targets. Because the bouncing ray method (Shooting and Bounce Rays) has the advantages of wide range of application, high computational efficiency and high accuracy, SBR is used to solve the electromagnetic scattering problem of composite targets. The research work of this paper is as follows: 1. In this paper, the history of the study on electromagnetic scattering from random rough surfaces is reviewed, and the corresponding calculation methods are introduced, and their application scope, advantages and disadvantages are summarized. Combined with the characteristics and attributes of random rough surface, it is decided that SBR is the focus of the study of electromagnetic scattering in this paper. 2. Due to the complexity of the shape characteristics of the composite target, the curvature information of the surface will be lost when it is dispersed by the plane triangular plane, thus the accuracy of the SBR calculation will be reduced. So that the solution of scattering body with concave structure will give the wrong results. In this paper, a virtual divergence factor (Virtual Divergence Factor,VDF) is introduced, which can correct the loss of curvature information and ensure the accuracy of SBR calculation. At the same time, because the composite targets are often electrically large, so there are a lot of triangular planes used to discretize them, so the Kd-tree data structure (traverse,ART) method is introduced to speed up the traversal of Kd-tree. Thus, the computational efficiency of SBR is greatly improved. 3. The improved SBR is used to calculate the radar cross section (RCS),) of a large number of typical targets. The results are in good agreement with the results obtained by the numerical method and the measured results. It is fully proved that the SBR has a wide range of applications. Excellent calculation efficiency and good accuracy. Finally, this method is successfully applied to the simulation of the composite target RCS composed of random sea surface and missile and ship respectively.
【學位授予單位】:電子科技大學
【學位級別】:碩士
【學位授予年份】:2015
【分類號】:TN011

【參考文獻】

相關期刊論文 前2條

1 夏明耀,伍振興;基于單積分方程矩量法的海洋表面微波散射模擬[J];電子學報;2005年03期

2 郭立新,徐燕,吳振森;分形粗糙海面高斯波束散射特性模擬[J];電子學報;2005年03期

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本文編號:2384641

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