新型压缩感知计算模型分析三维电大目标电磁散射特性  

Novel compressive sensing computing model used for analyzing electromagnetic scattering characteristics of three-dimensional electrically large objects

作　　者：王攀 王仲根[1] 孙玉发[2] 聂文艳 Wang Pan;Wang Zhong-Gen;Sun Yu-Fa;Nie Wen-Yan(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China;School of Electronics and Information Engineering,Anhui University,Hefei 230601,China;School of Mechanical and Electrical Engineering,Huainan Normal University,Huainan 232001,China)

机构地区：[1]安徽理工大学电气与信息工程学院,淮南232001 [2]安徽大学电子信息工程学院,合肥230601 [3]淮南师范学院机械与电气工程学院,淮南232001

出　　处：《物理学报》2023年第3期9-16,共8页Acta Physica Sinica

基　　金：国家自然科学基金(批准号:62071004);安徽省自然科学基金(批准号:2108085MF200);安徽高校自然科学重点项目(批准号:KJ2020A0307)资助的课题。

摘　　要：为提高基于压缩感知技术的矩量法在三维电大目标双站电磁散射问题中的计算效率和稳定性,提出新的稀疏、测量和重构方法,构建一种新型压缩感知计算模型.不同于基于欠定方程的传统的压缩感知计算模型,新型计算模型首先采用按行均匀抽取阻抗矩阵的方法构造测量矩阵以获得稳定的计算结果;然后,基于Foldy-Lax方程生成多阶特征基函数并作为稀疏基对感应电流进行稀疏转换;再依据少数低阶特征基函数足以近似表征感应电流的先验条件,将恢复算法简化为最小二乘法;最后,将矩阵方程转换为一个超定系统并采用最小二乘法解出电流系数.与传统的计算模型相比,新型计算模型不仅可以获得更加稳定的精确解,还可以显著提高电大目标双站散射问题的求解效率和计算精度.数值仿真结果证明了新方法的可行性和高效性.The method of moments is one of the most effective algorithms for solving electromagnetic scattering problems.However,the high computational complexity limits its application to electrically large problems.As an improved algorithm,the compressive sensing-based method of moments introduces the compressive sensing technique into the algorithmic structure,which avoids the inverse of the matrix equation and improves the computational efficiency.Using the under determined equation-based calculation model,this scheme is utilized to efficiently analyze the bistatic scattering of the objects.In this technique,the extracted few rows from the impedance matrix are used to construct the measurement matrix.Nevertheless,the results are unstable due to the random extraction utilized to build the measurement matrix.Furthermore,it is challenging task to provide an appropriate sparse basis for the induced currents of three-dimensional objects discretized by the Rao-WiltonGlisson basis functions.To address the aforementioned issues,a novel compressive sensing calculation model that enhances measurement matrix building,sparse basis construction,and recovery is provided in this paper.First,several rows of the impedance matrix are uniformly extracted to produce consistent computation results,which is opposed to the randomly constructed measurement matrix in the conventional technique.The number of rows to be extracted is typically set to be 3-5 times the number of basis functions for high accuracy.Then,the characteristic basis functions based on the Foldy-Lax equation are employed to construct the sparse basis.Considering the prior knowledge that the lower order characteristic basis functions are dominant,the columns of the recovery matrix corresponding to some low-order characteristic functions are determined in advance as the columns that will be identified by the recovery algorithm,thus simplifying the recovery algorithm to a leastsquares operation.Obviously,the matrix equation is reduced to an over determined equation instead of t

关 键 词：压缩感知 矩量法 特征基函数 测量矩阵 

分 类 号：TN011[电子电信—物理电子学]