Research On High-precision 3-D Imaging And Scattering Characteristics Of Radar Targets

The research on three-dimensional(3-D)imaging and scattering characteristics of radar targets mean in-depth analysis of spatial scattering characteristics by combining the3-D test systems and 3-D radar imaging technology.This research helps evaluate the stealth performance of targets or the anti-stealth performance of radar systems,which can provide new technical approaches for several applications,e.g.,radar cross section(RCS)measurements,radar target detection and identification,assessment of stealth coating absorption,counter-terrorism,and security screening.The key to this research is how to obtain precise radar 3-D imaging results and their relationship with the scattering characteristics,which is still in its infancy.This paper combines the theories and technologies of electromagnetic scattering and radar imaging to research high-precision 3-D imaging and scattering characteristics of radar targets.The main research contents and contributions include:1)The problem of near-field RCS measurement uncertainty is studied,the measurement uncertainty estimation models for the uncertainty factors in the 3D imaging of radar targets are established,and finally,the source and numerical range are determinedThis research adopts a new 3D test system,which is generally implemented under near-field conditions.Thus,the sources and uncertain factors of measurement errors are different from those of classical RCS tests.At present,a comprehensive and systematic analysis has not been carried out,and an effective evaluation system and standard have not been formed.Aiming at these problems,first,the uncertainty factors during near-field measurements are decomposed by combining the basic theory of uncertainty,mainly including the environmental factors,near-field factors,radar system factors,and data processing factors;secondly,some uncertainty estimation models(e.g.,targetbackground interaction,near-field uncertainties,and imaging ambiguity)are derived;then,the uncertainty estimation model is tested through electromagnetic simulations and real measurement experiments;finally,the range of uncertainty values in near-field RCS measurements is determined.2)The transformation from scattering coefficient to RCS is studied,and an RCS transformation method based on near-field 3D imaging is proposedOn the one hand,the scattering coefficients with the spatial distribution obtained by near-field 3-D imaging have different physical meanings from the RCS obtained by farfield methods,and the transformation between the two is not clear;on the other hand,there are several problems(e.g.,side lobe crosstalk and ripple disturbance)in 3-D imaging,which also affect the measurement accuracy.For these problems,the Mie-series interpolation-based Back Projection(BP)algorithm is used to suppress the side flap;secondly,the law of Gibbs effect is used to establish a two-dimensional window function to suppress ripple disturbance;finally,the weighted Green's function is used to compensate the near-field 3D imaging results and to complete the transformation from scattering coefficient to RCS.The results show that the proposed method can effectively implement the RCS test through electromagnetic simulation,actual test,and comparison with traditional test methods.3)The calculation problem of the scattering coefficient affected by 3-D spherical wave effects is studied,and a near-field 3-D imaging algorithm via the dyadic Green's function is proposed to further improve the imaging accuracyThe scattering coefficient of targets will inevitably be affected by 3-D spherical wave effects when the test is in near-field conditions.Conventional microwave 3-D imaging algorithms(e.g.,BP algorithm)only compensate for the phase information caused by the distance change,but do not compensate for the relative amplitude difference caused by the 3-D spherical wave effects,which limits the accuracy of scattering coefficient calculation.Thus,a near-field 3-D imaging method is proposed based on the Dyadic Green's Function(DGF).A novel spherical wave vector compensation operator is designed based on dyadic Green's function method,which solves the problem of scattering coefficient calculation caused by the 3-D spherical-wave effects,thus the accuracy of 3-D imaging is further improved.4)The limitation of imaging resolution on the accuracy of scattering characteristic measurement is studied,and an adaptive parameter optimization Bayesian learning 3-D imaging method is proposed to further improve the measurement accuracyThe resolution and side-lobes are one of the important factors affecting the radar 3-D imaging-based measurement accuracy,while traditional matched-filtering 3-D imaging methods are limited by Rayleigh resolution(i.e.,the presence of the main-lobe width and side-lobe crosstalk),which has become a bottleneck to further improve measurement accuracy.Thus,an RCS test method is proposed based on an adaptive parameter optimization Bayesian learning method.First,this method employs the data block to ensure the phase consistency of data processing;second,the initial parameters of each data block are optimized based on a Bayesian information criterion so that the block-based parameter adaption is realized,which enhances the accuracy and stability;finally,combining the near-field and far-field transformation method with the sparse Bayesian learning 3-D imaging result,the RCS measurement accuracy can be further improved compared to existing methods.In summary,this dissertation solves a series of problems in high-precision microwave 3-D imaging and scattering characteristics and has achieved some contributions.The above work provides theoretical and technical support to enhance radar detection performance,improve the measurement schemes of radar target scattering characteristics,and reduce the difficulty of the development and maintenance of stealth equipment.