Research On Three Dimensional Imaging RCS Measurement Technology Based On Sidelobe Suppression

With the development of radar technology and the improvement of radar detection ability,the accurate estimation and measurement of radar cross section(RCS)become more and more important.RCS measurement technology based on three-dimensional imaging is a new real,efficient and more flexible RCS measurement technology in recent years.In this technology,the target and background noise are separated by 3D high-resolution imaging,and the accurate RCS of the target is obtained by near-field and far-field transformation algorithm.The imaging accuracy of RCS measurement based on imaging directly affects the measurement accuracy of RCS.However,traditional imaging methods inevitably have side lobe interference.Therefore,in order to obtain high-precision RCS,it is necessary to suppress the sidelobe in imaging.In order to solve this problem,this paper starts with clean algorithm and compressed sensing and other imaging sidelobe suppression methods to improve the imaging quality and ultimately improve the RCS measurement accuracy.The main work and innovation of this paper are summarized as follows:1.The RCS measurement model based on three-dimensional synthetic aperture imaging,the antenna working mode and signal model are summarized.A back projection(BP)imaging algorithm is introduced,and the accurate phase compensation can be made for each point in the imaging.Based on the algorithm,the threshold based method of scattering center extraction is studied,and it is pointed out that the method can not suppress the sidelobe effectively.Then,the influence of sidelobe on RCS measurement accuracy is verified by simulation,which proves that the sidelobe can reduce the accuracy of RCS inversion based on imaging.At last,a traditional method of sidelobe suppression with window is introduced,but the method reduces the resolution of image while suppressing sidelobe.2.In order to solve the problem of the method of adding window to suppress the sidelobe,clean algorithm is used to suppress the sidelobe.This paper first introduces the principle and general steps of the clean algorithm for sidelobe suppression,and points out that the clean algorithm may contain estimation error.Then,an improved coherent clean algorithm is proposed,which uses the operation of re evaluating the previous point to improve the accuracy of the algorithm.As the selection of PSF directly affects the accuracy of clean algorithm,this paper gives the accurate PSF of 3D BP imaging,which provides a favorable condition for the accurate extraction of scattering points.Finally,this paper analyzes the computational complexity and accuracy of the algorithm,and verifies that the clean algorithm can improve the RCS measurement accuracy based on imaging through simulation.3.In order to solve the problem of large computation and estimation error of clean algorithm in complex scenes,compressed sensing theory is introduced to overcome the defects of traditional 3D imaging technology and achieve the effect of suppressing sidelobe.Starting from the original echo directly,the observation constraints of echo measurement signal and scene scattering coefficient are established,and the echo observation matrix based on 3D imaging is designed.The scattering center extraction based on compressed sensing imaging is verified by MATLAB simulation.The relationship between RCS inversion value and reference value is analyzed by FEKO simulation,which proves that improving imaging resolution is helpful to improve RCS inversion accuracy.Then,a super-resolution compressive sensing method is proposed.When the scene is divided into finer grids and solved,the RCS inversion accuracy is further improved.