自适应交叉近似算法在矩量法中的应用

矩量法(Method of Moment, MoM)计算电大目标辐射与散射问题时消耗计算机资源巨大。采用自适应交叉近似算法(Adaptive Cross Approximation Algorithm, ACA)降低了MoM计算电大问题时的内存需求与计算复杂度,借助NURBS(Non-Uniform Rational B-Splines，NURBS)建模方法设计了形状规则且边界清晰的ACA三维分组方法,从而实现了基于矩量法的ACA算法。通过算例证明该方法在不损失MOM的计算精度的前提下有效地降低了存储空间和计算量,并通过与商业软件计算结果对比,验证了算法准确有效。

The Application of Adaptive Cross Approximation Algorithm for Method of Moment

Method of moment (MoM) expends large computer resource when calculating radiation and scattering problem of large target. The adaptive cross approximation (ACA) algorithm is applied to compress the distant field rank-deficient sub-matrices of the impedance matrix through linear algebra manipulations, which reduces memory needs and calculation complexity in MoM when computing electrically large problem. The RWG (Rao-Wilton-Glisson) triangle spaces are grouped according to the Non-Uniform Rational B-Splines (NURBS) spaces by means of NURBS modeling method. The grouping method is designed to realize the ACA algorithm based on MOM, which could make the subgroups more regular and clearer on the boundary line. Numerical examples are performed, the results show that this method can be the same with MoM in computation precision, and simultaneously the memory and compute time are reduced by this method. RCS (Radar Cross Section) of electrically large metal missile calculated by using this method is in good agreement with the result calculated by the commercial software, which shows that the algorithm is accurate and effective.