| Aerospace targets refer to targets such as airplanes,airships,man-made aircraft,and space debris.With the development of transfer aerospace technology,competition and the increase of space debris,the safety of man-made aircraft has been threatened by all aspects.Tracking,monitoring and imaging the motion state of aerospace targets is one of the important aspect of guarding the artifiial aircraft.Inverse Synthetic Aperture Radar(ISAR)plays an irreplaceable role in both military and civilian remote sensing with its advantages of day and night,and all-weather working.Through the ISAR high-resolution imaging and motion parameter estimation of aerospace targets,it can provide strong support for future target classification,identification and cataloging.Therefore,the ISAR high-resolution imaging and motion parameter estimation of aerospace targets are useful for national defense and civilian livelihood.Under the support of several projects,e.g.Electromagnetic interpretation,Target Three Dimension(3D)reconstruction based on Multi-band radar sequence diagram,and Interferometric ISAR(In ISAR)3D imaging,this dissertation focuses on three aspects,i.e.the motion parameters of aerospace targets,the multi-view imaging based on attribute scattering center model,and the 3D imaging of aerospace targets.The main contents of this dissertation are summarized as follows:1.This part introduces the development of Synthetic Aperture Radar(SAR)and ISAR at home and abroad.The main purpose of this dissertation is subsequently shown.2.The basic concepts of ISAR imaging are discussed,and the existing ISAR motion compensation algorithms and common imaging methods are summarized,which paves the way for the following chapters.3.In the field test,the radar echo data of ballistic target is very large and the target is small,so the effective information in the vast echo data is very limited.How to quickly locate and separate the effective information in a short time has become the first difficult problem in outfield experiments.To solve this problem,this paper focuses on group of ballistic target fine motion compensation in wide-narrow band system.In this chapter,random Hough transform and Time Varying Auto-Regressive model(TVAR)algorithms are used to estimate and compensation the group of ballistic targets.In the wideband direct sampling model,the amount of echoes is huge.In addition,the scattering point migration of ballistic target results in serious micro motion and dramatically spectrum changing for wideband radar echoes in field experiment.In such case,the traditional motion compensation methods are unsuitable anymore and it is difficult in processing wideband direct sampling data.In practical application,narrow-band radar has a series of advantages,such as long-distance measurement,wide range tracking,flexible working mode,but low resolution.The wideband radar has the advantage of high resolution,so it is mostly used for accurate monitoring,tracking and target recognition.The disadvantages are that the cost of radar is too high,the echo signal model is complex,and the processing process is difficult,which is not conducive to popularization.Therefore,it is necessary to combine the wide and narrow band radars to make full use of their advantages.Also,there is already wide-narrow band radars.Firstly,random Hough transform is used on narrowband signal to separate group targets.The targets location corresponding to wideband sigle,the coarse motion compensation and sigle extarction are subsequently carried out.Further compensation is then made upon the extracted signal by gravity center method.The residual motion parameters and smooth micro-Doppler(m-D)feature curve can be obtained by performing timefrequency analysis based on the TVAR.The m-D parameters are used to compensation the target signal accurately.Finally,CADFEKO simulation results verify the effective of the proposed method.4.At present,the existing large angle imaging and multi view fusion mainly use image fusion,which is sensitive to noise and is not conducive to target recognition.To solve this problem,This paper introduces the component parameter fusion of multi view attribute scattering center model(ASCM)to achieve the effect of two-dimensional ISAR image fusion.Traditional point scattering model can only represent the position information of the scatterer,but the geometric characteristics of the target is not represented.In order to extract all the views of the target's components and overcome the phenomenon of anisotropy,occlusion and week scattering points being submerged,an algorithm for extracting and fusion of ASCM parameter set is proposed.First,the full aspect data is divided into several overlapping sub-aspect and estimate the parameters of each sub-apertures.Then the subaperture's parameters are projected into the same coordinate system.Finally,all parameters are fused into a parameter set.The proposed method can get a parameter set,which can be used for radar echo inversion,improving the visualization of the radar image,target recognition and classification.Simulation validates the effectiveness of the novel approach.5.Due to the limitation of equipment resources,in the case of single base radar,the problem of 3D reconstruction and attitude estimation of radar sequence diagram in target coordinate system is divided into two aspects: 3D reconstruction and attitude estimation based on radar sequence diagram.Fist,this paper proposed a three dimension(3D)reconstruction based on radar sequence.Generally speaking,3D imaging of spinning space target is obtained by performing matrix factorization method on the scattering trajectories obtained from sequential radar images.Because of the errors of scattering center extraction and association,the 3D reconstruction accurate will be reduced or even fail.In addition,the scattering center trajectory from turntable target consists with circle nature,which is inconsistent with the elliptic property of the scattering center trajectory obtained by optical geometry projection.To tackle these problems,this paper proposes a short time 3D reconstruction method of space target.In addition,the attitude of the obtained target 3D reconstruction is uncertain.Through further constraints on the projection matrix,the target 3D reconstruction attitude is obtained.Through sequence 3D reconstruction and attitude estimation,the fusion of multi-view 3D reconstruction results is realized,and the obtained target information is further increased.6.Due to the different imaging mechanisms,ISAR images do not have strict gray similarity like optical images.The optical image matching algorithm is not suitable for ISAR image matching because of its less obvious points and complex scattering characteristics.To solve this problem,this paper focuses on ISAR image matching and Bistatic 3D imaging by Random Sampling Consistency Algorithm(RANSAC).First,taking advantage of ISAR image sparsity,radar images are converted into scattering point sets.Then,a coarse scatterer matching based on RANSAC is performed.Based on the coarse scatterer matching,an approximate angle of incidence is estimated.Through the iterative estimation of the radar incident angle and the height of the scattering point,when the changes of estimated value is smaller than a preset value,the height of the scattering point and the precise radar incident angle can be estimated at the same time.Finally,an experiment was conducted based on the electromagnetic simulation software CADFEKO,which proved the effectiveness of the algorithm. |
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