Research On ISAR Imaging And Cross-range Scaling Of Space Targets

Space objects mainly include air-planes and other aerial targets,artificial satellites and other orbiting objects and trajectory objects.Inverse synthetic aperture radar(ISAR)imaging is able to obtain high-resolution images with distinct structural features of space objects,thus makes great contributions to surveillance and recognition of space objects.Therefore,ISAR imaging of space targets plays an extremely important role in strategic defense,anti-missile and exploration of deep space.This dissertation mainly focuses on ISAR imaging and cross-range scaling of space objects.The main content of this dissertation is summarized as follows.Chapter 1 is the introduction.It reviews the research background of ISAR.The ISAR research status both at home and abroad are introduced.Morever,space target radar surveillance systems are introduced.Lastly,main contents of this dissertation are presented.In chapter 2,the ISAR compensation technology is studied.The theoretical basis of ISAR range alignment technology and ISAR phase compensation technology is studied firstly.Then,the ISAR real data of air-planes validates several range alignment methods and phase compensation methods.At the same time,a new range alignment method of space target capable of eliminating jump and drift errors is proposed in this dissertation.Both drift errors and jump errors will lead to the ghost targets and defocusing of ISAR images.At last,processing results of simulation data of trajectory objects and orbiting objects are presented to show the superiority of the proposed algorithm.In chapter 3,the cross-range scaling methods for ISAR images of space objects are studied.Firstly,the principle of ISAR cross-range scaling is analyzed.According to the characteristic that the range-doppler image of space trajectory objects takes up a large number of range cells,the method for cross-range scaling by analyzing the relation between the chirp rate of the cross-range signal and the range cell is proposed.Acoording to the characteristic that the range-doppler image of space target has distinct structure feature,the image based method for cross-range scaling by feature matching is presented.Finally,experimental results with both simulated data of orbiting objects and real data of air-planes are provided to demonstrate the effectiveness and robustness of the two methods.In chapter 4,the implementation of ISAR imaging algorithm based on GPU architecture is studied in order to meet high-quality and real-time processing requirements.Firstly,the principle of GPU parallel computing based on CUDA environment is introduced.Secondly,the ISAR Range-Doppler algorithm is introduced and the inherent parallel nature of Range-Doppler algorithm is analyzed.Thirdly,a scheme suitable for GPU acceleration is proposed.Finnaly,the GPU acceleration method is integrated into MFC framework.Chapter 5 is the conclusion,the work of this dissertation is summarized and the future work is pointed out.