Study On Inverse Synthetic Aperture Radar Imaging And Methods Of Azimuth Scaling

This thesis focuses on the azimuth scaling methods for Inverse Synthetic Aperture Radar(ISAR) imaging, both theoretical study and numerical simulation are carried out as well as real data processing results are presented. The major works and contributions are as below:First, the theoretical basis of ISAR is studied, including basic imaging theory of ISAR, among which the geometrical model of ISAR and signal model are introduced in detail. Besides, range compression methods and translational motion compensation methods are also studied and accompanied by simulation experiments.Second, imaging algorithms for ISAR are studied, including Polar Format Algorithm, Time-Frequency Analysis and Keystone Transformation algorithm, which are demonstrated through simulation experiments.Third, the azimuthal scaling methods for ISAR are studied including rotation angle estimation based on phase information, rotation velocity estimation based on line feature as well as rotational angle estimation based on point feature. Both simulation and real data experiments are presented.Fourth, we proposed a robust rotational angle estimation method by minimizing the weighted error function based on two-direction rotation factor. The proposed algorithm first utilizes the Range-Doppler imaging algorithm to get image which is then divided into different series. Second, the optimal rotation angle between different images is estimated via bi-direction weighting error function minimization. Both simulation and real data processing results are presented to show the effectiveness and robustness of the method.