二维多粗糙度分层粗糙面与上方目标复合电磁散射计算方法

研究了二维多粗糙度分层粗糙面与上方目标复合电磁散射特性的自适应迭代物理光学算法。采用Monte Carlo法并结合高斯谱函数生成高斯粗糙面，基于分区域建模方法，建立了二维多粗糙度分层粗糙面和上方目标的复合模型。利用物理光学法和等效原理，得到分层粗糙面和目标的直接感应电磁流；基于表面积分方程，分析了分层粗糙面之间以及粗糙面和目标之间的耦合电磁流迭代机理。引入感应电磁流能量改变速率，对传统迭代物理光学法进行改进，使算法自动收敛。将计算结果同多层快速多极子方法和迭代物理光学法进行比较，验证了算法的准确性和高效性。在此基础上，研究了不同目标、不同粗糙度的分层粗糙面的双站RCS计算结果和散射特性，讨论了分层粗糙面间距对双站RCS计算结果和散射特性的影响。本研究为分层环境及上方超低空突袭目标的探测、分类和识别提供了数据支撑和理论基础。

A Calculation Method of Composite Electromagnetic Scattering from Two Dimensional Multi Roughness Layered Rough Surface and Target Above

An adaptive iterative physical optics algorithm is proposed by studying the complex electromagnetic scattering characteristics of two dimensional multi roughness layered rough surface and target above, and a composite model of two dimensional layered rough surface and the target above is established by adopting the Monte Carlo method in combination with the generated Gaussian rough surface with Gaussian spectrum function based on sub regional modeling method. The direct induced electromagnetic current of the layered rough surface and the target is obtained by using the physical optics method and the equivalence principle. Based on the surface integral equations, the iterative mechanism of the coupled electromagnetic current between the layered rough surfaces and between the rough surface and the target is deduced. The traditional iterative physical optics method is improved by introducing the change rate of induced electromagnetic current energy, making the algorithm convergent automatically. The results are compared with those of the multi level fast multipole algorithm and iterative physical optics method, and the accuracy and efficiency of the algorithm are verified. On this basis, the bistatic RCS calculation results and scattering characteristics of layered rough surfaces with different targets and different roughness are studied. The effect of the distance between layered rough surfaces and on the bistatic RCS calculation results and scattering characteristics is discussed. This study provides data support and theoretical basis for the detection, classification and recognition of ultra low altitude targets above a layered environment.