复杂天线平台一体化数值建模是电子信息领域中迫切需要解决的热点问题之一。然而，由于材料、结构的复杂以及几何上的多尺度特性，传统数值方法求解该问题时不仅计算效率低下，而且几何建模也十分繁琐复杂。为了解决该类难题，项目拟基于积分方程区域分解法（IE-DDM）框架开展相应研究。具体包括：（1）针对多层介质罩的电磁散射，研究一种仅由传输条件耦合连接的新型多区域积分方程区域分解方法（MT-DDM），以提高传统方法的求解效率，简化几何建模。（2）探索由传输条件全局、局部耦合连接的混合方程区域分解算法（HyE-DDM），适用于微带天线和平台一体化散射、辐射计算。（3）研究区域分解算法的预条件技术以改善矩阵的迭代收敛性。最终，发展出用于复杂天线平台及介质罩一体化精确高效计算的非重叠、非共形区域分解方法。研究成果将用于复杂天线平台的雷达特性分析及电磁兼容计算等方面，具有重要的学术意义和实际工程价值。

The electromagnetic modeling of the integrated model of antennas and platforms is one of hot topics in modern electronic information area. However, these integrated models are always typical multi-scale objects. They include not only complex materials but also complex geometric structures. If traditional numerical methods are used to solve these multi-scale problems, it is very hard to generate high-quality meshes and will also lead to ill-conditioned matrices. To solve the above problems, we will conduct the following research under the integral equation domain decomposition method (IE-DDM) framework:. (1) The multiple-traces domain decomposition method (MT-DDM) will be developed for solving the electromagnetic scattering from multi-layers dielectric objects. In the MT-DDM, only transmission conditions (TCs) are used to enforce the continuity of fields. The MT-DDM can not only simplify the geometric modeling procedures but also improve the efficiency of electromagnetic modeling.. (2) A global-local coupling hybrid equations domain decomposition method (HyE-DDM) will be developed for the electromagnetic modeling of integrated model of microstrip antennas and platforms. . (3) High efficient preconditioners will be developed to improve the iterative convergence property of domain decomposition method.. This research will build robust and efficient numerical tools available for analysis of integrated model of complex antennas and platform, in the framework of IE-DDM. The research achievements will be widely applied in the radar characteristic computation and electromagnetic compatibility simulation of complex objects, and have very important academic and application value.