Accurate analysis of bistatic scattering problems using compressive sensing with a new sparse basis

Abstract

Compressive sensing (CS) used as a sparse basis can enhance the characteristic basis functions (CBFs), which helps in analyzing the bistatic scattering problems of a three-dimensional (3D) object. However, a sparse basis constructed by the CBFs lacks current information under a single plane wave, leading to a low computation accuracy when analyzing complex objects. To resolve this issue, a new sparse basis construction method is presented in this work, which considers the current information under multilevel plane waves with different incident angles and different polarization modes. As this new sparse basis contains more comprehensive current information, the accuracy is considerably improved when analyzing the complex targets. Furthermore, the accuracy and efficiency of the proposed method are verified by extensive numerical simulations.

KEYWORDS:

• Compressive sensing
• sparse basis
• characteristic basis functions
• singular value decomposition

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the Anhui Provincial Natural Science Foundation of China under Grant 2108085MF200, in part by the National Natural Science Foundation of China under grant number 62071004, in part by the Natural Science Foundation of Anhui Provincial Education Department under grant number 2022AH051583 and 2022AH052138.