Communication Bistatic RCS Estimation Using Monostatic Scattering Centers With Compressive Sensing

This communication presents a novel technique for obtaining bistatic radar cross sections (RCSs) extracted from a monostatic scattering field dataset using a discrete scattering center model and basis pursuit denoising (BPDN) algorithm, which is compressive sensing (CS) technique. With the high-frequency assumption, a complex vector of independent point sources is formulated in a monostatic configuration for a geometrical relationship among the transmitter, receiver, and equivalent scatterers. A matrix equation for the scattering problem of an underdetermined form is effectively calculated by an iterative BPDN solver. Then, compensating the phase difference in the bistatic condition can derive the bistatic RCS at specific frequency points and observation angles. The accuracy of the proposed method for extracting bistatic results is verified using two numerical examples, and the performance of the method in terms of measurement efficiency and data resolution in frequency and angle domains is compared with that of conventional method.

Automated summary

This paper presents a novel technique for extracting bistatic radar cross sections (RCSs) from a monostatic scattering field dataset using a discrete scattering center model and basis pursuit denoising algorithm. The accuracy and performance of the proposed method are verified through numerical examples.