In this letter, the characteristic basis functions (CBFs) are utilized to enhance the compressive sensing (CS) technique to analyze the bistatic scattering problems of three‐dimensional targets. The CS technique can efficiently analyze the bistatic scattering problems by establishing an underdetermined linear equation instead of traditional full‐rank dense impedance matrix equation. However, the CS method is limited to two‐dimensional targets. The reason is that the induced currents of the three‐dimensional target expressed by Rao‐Wilton‐Glisson basis functions are not sparse on the commonly sparse basis, since the field source has no orderly distribution when the target is modeled and discretized by commercial software. In order to solve this problem, the CBFs are used in this letter as the sparse basis to improve the sparsity of the induced currents. The numerical results of different targets are presented to validate the accuracy and efficiency of the proposed method.

中文翻译：

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特征基函数增强了压缩感测，用于解决三维目标的双基地散射问题

在这封信中，利用特征基函数（CBF）来增强压缩感测（CS）技术，以分析三维目标的双基地散射问题。CS技术可以通过建立一个不确定的线性方程而不是传统的全秩密集阻抗矩阵方程来有效地分析双站散射问题。但是，CS方法仅限于二维目标。原因是由Rao-Wilton-Glisson基函数表示的三维目标的感应电流在通常的稀疏基础上并不稀疏，因为当用商业软件对目标建模和离散化时，场源没有有序分布。为了解决这个问题，在本文中，将CBF用作稀疏基础以提高感应电流的稀疏性。给出了不同目标的数值结果，验证了所提方法的准确性和有效性。