Research On Three-dimensional Imaging And Rotation Estimation Of Space Target Using Inverse Synthetic Aperture Radar

Traditional inverse synthetic aperture radar(ISAR)can obtain two-dimensional high-resolution images of spatial non-cooperative targets at all-weather and all-time.However,such two-dimensional images are projections of spatial targets on the image projection plane.Therefore,it is impossible to obtain the information of the target in a high dimension.ISAR three-dimensional(3D)imaging technology can obtain 3D structure information of non-cooperative targets.On this basis,the rotational vectors of the targets are estimated to provid the precise structural information and movement states of the targets.This thesis focuses on the research of ISAR 3D imaging and rotational vector estimation,especially discusses the“L-shaped”three-antenna interferometric ISAR(In ISAR)3D imaging method,the ISAR 3D imaging method based on null space l₁ norm minimization under the framework of compressed sensing(CS),and the rotational velocity estimation method based on micro-Doppler feature extraction.First,the basic principles of ISAR imaging technology are briefly explained.Then the research status of ISAR 2D and 3D imaging at home and abroad is analyzed.And the research background and content of the thesis are introduced.Next,the“L-shaped”three-antenna In ISAR 3D imaging system is studied,and the basic principles and specific implementation steps of 3D imaging are given.The multi-channel“CLEAN”technique is used to extract strong scatterers.The interferometric phase information is used to obtain the 3D image of the target.At the same time,the effective rotational vector of the target is estimated.3D imaging is performed using the simulation data of the satellite target in different imaging scenarios.The experimental results show that the method has good performance of 3D imaging and effective rotational vector estimation.In order to solve the problem of increased data caused by the multi-antenna In ISAR,the ISAR3D imaging method based on null space l₁ norm minimization under the framework of CS is studied.First,under sample the ISAR data of each channel.The solution of the underdetermined image of each channel is decomposed into two parts:the preliminary value and the residual value.First,the weighted lease square method is used to estimate the preliminary value,which is used as the target initial image.And KF iteration is used to estimate the solution of residual value in null space.Then the reconstructed 2D images are used to obtain the 3D image of the target by the method of interference.The imaging results of simulation data show that the method can get good imaging results under different under-sampled rate.At the same time,reducing the null space dimension can greatly improve the efficiency of the algorithm.On the basis of obtaining the effective rotational vector of the non-cooperative target,the rotational velocity estimation method based on micro-Doppler feature extraction is studied.The micro-Doppler phenomenon of radar target and the one-dimensional range profile series modulation model under the chirp signal are discussed.It can be found that the micro-Doppler frequency periodically changes with time and is consistent with the rotational period of the target.The short time Fourier-transform(STFT)is used to extract the micro-Doppler frequency variation period to achieve the rotational velocity estimation.Thus,the total rotational vector estimation of the non-cooperative target in 3D space is completed.The simulation data processing results show that the algorithm can get precise target rotational vector estimation.Finally,the work of the thesis is summarized,and the problems that need further research are pointed out.