Study On High Resolution Radar Unambiguous Imaging And Motion Compensation

Synthetic aperture radar and inverse synthetic aperture radar (SAR/ISAR) imaging systems have the abilities of all-time, all-weather and long-range illumination, as well as two dimensional (2-D) high-resolution imaging, etc. The dramatic improvement of the modern radars in information acquisition have led to wide applications in the national defense and civil industries.Image resolution is one of the most important indicators in SAR and ISAR imaging. The demand on higher resolution has put increasing burdens on radar systems and growing need for accurate and stable motion compensation techniques. Among the methods of phase error compensation, the compensation precision and computational efficiency is a paradox. Among the methods of phase error compensation, the compensation precision and computational efficiency is a paradox, greatly restricting the application in reality. When the radar works at highly squinted mode or wide beam mode, the phase errors are azimuth-variant, which brings great challenges in obtaining high resolution images of targets.Modern multi-function ISAR are able to realize wide-swath surveillance, multi-target tracking and imaging. But when ISAR tracks and observes a single target, the wide-band measurement for the single target is limited and the aperture is sparse because of its time-sharing system switching between search pattern and image pattern. The migration through range cells (MTRC) is also presented as the target’s motion is non cooperative. When ISAR illuminates multiple targets, the Doppler ambiguity inevitably occurs to avoid range ambiguity. The MTRC with Doppler ambiguity is also needed to be solved in the process of ISAR imaging.This dissertation focuses on the study of the problems mentioned above and also involve the new techniques of phase error compensation, including azimuth-invariant and azimuth-variant phase error compensation algorithms, the sparse-aperture high resolution imaging and MTRC compensation, Doppler ambiguity removal and high resolution imaging of group targets with MTRC compensation. The main content of this dissertation is summarized as followsThe first part focuses on azimuth-invariant phase error compensation method. The eigenvector method for maximum-likelihood estimation of phase error can obtain ideal performance of phase error estimation by using the eigenvector corresponding to its largest eigenvalue. Although it has accurate estimation and good robustness, it requires eigen-decomposition of the sample covariance matrix, which is a computationally expensive task limiting its real-time applications. A weighted maximum norm method (WMNM) for phase error estimation and compensation is proposed in the second section. The optimally estimated phase error can be obtained directly by solving the maximum norm L-2. This method gets rid of the eigen-decomposition of the sample covariance matrix and reduces the computational cost greatly. By adding different weights to each range bin, the contribution of the range cells with high signal-to-noise ratio (SNR) will be enhanced. Finally, the estimation accuracy of the phase error can be improved.The second part focuses on Azimuth spatial-variant (ASV) phase errors compensation method. Usually, ASV is produced by both platform velocity and acceleration, and traditional phase error compensation algorithms are implemented based on the models that ignore the azimuth variation of phase errors. Even using the subimage strategy, it is difficult to obtain an optimal autofocusing result when ASV phase errors present. In the third section, we propose a phase error compensation algorithm for correcting the ASV phase error within SAR image. By utilizing universal parametric phase error model, the contrast maximization cost function for estimating the ASV phase error is established. And a gradient-based solver of this optimization is also developed. The proposed algorithm is capable of focusing SAR image with ASV blurs within a few iterations.The third part focuses on ISAR imaging of manoeuvring targets with MTRC compensation. In ISAR imaging of a target with significant manoeuvres, severe MTRCs and time-varying Doppler usually present in the echoed signal. Both of them may challenge the conventional motion compensation and imaging methods, which are usually based on the assumption of small rotational angle with short coherent time duration. Moreover, for a multi-functional ISAR, full aperture (FA) data collection might be unachievable because of the conflict with other radar activities, resulting in sparse aperture (SA) data. In the forth section, an ISAR imaging method of manoeuvring targets with SA data is proposed, where MTRC compensation and time-varying Doppler are well accounted. By using a sparse Chirp-Fourier basis with first-order range-azimuth coupling term, an improved orthogonal match pursuit (OMP) algorithm is implemented to solve the sparsity-driven optimisation for FA data reconstruction from SA-ISAR measurements. As a primary item, MTRC compensation is seamlessly embedded into the FA signal reconstruction for ISAR imaging of manoeuvring targets.The fourth part focuses on Doppler Ambiguity Removal and ISAR Imaging of group targets with sparse decomposition. Low pulse repetition frequency (PRF) waveforms inherently lead to the Doppler ambiguity in inverse aperture radar (ISAR) imaging of group targets. In the fifth section, a novel Doppler ambiguity removal method with sparse decomposition is presented for ISAR imaging of group targets. By solving a sparsity-driven optimization problem, Chirp signals corresponding to scattering centers of group targets are extracted exactly in azimuth, and the Doppler ambiguity number of each extracted Chirp signal can be estimated simultaneously in the process of sparse decomposition. As a result, unambiguous ISAR image of group targets can be well reconstructed and focused by a sophisticated compensation of migration through range cells and the time-varying Doppler.