Computational Algorithms for Improved Synthetic Aperture Radar Image Focusing

High-resolution radar imaging is an area undergoing rapid technological and scientific development. Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) are imaging radars with an ever-increasing number of applications for both civilian and military users. The advancements in phased array radar and digital computing technologies move the trend of this technology towards higher spatial resolution and more advanced imaging modalities. Signal processing algorithm development plays a key role in making full use of these technological developments.In SAR and ISAR imaging, the image reconstruction process is based on using the relative motion between the radar and the scene. An important part of the signal processing chain is the estimation and compensation of this relative motion. The increased spatial resolution and number of receive channels cause the approximations used to derive conventional algorithms for image reconstruction and motion compensation to break down. This leads to limited applicability and performance limitations in non-ideal operating conditions.This thesis presents novel research in the areas of data-driven motion compensation and image reconstruction in non-cooperative ISAR and Multichannel Synthetic Aperture Radar (MSAR) imaging. To overcome the limitations of conventional algorithms, this thesis proposes novel algorithms leading to increased estimation performance and image quality. Because a real-time imaging capability is important in many applications, special emphasis is placed on the computational aspects of the algorithms.For non-cooperative ISAR imaging, the thesis proposes improvements to the range alignment, time window selection, autofocus, time-frequency-based image reconstruction and cross-range scaling procedures. These algorithms are combined into a computationally efficient non-cooperative ISAR imaging algorithm based on mathematical optimization. The improvements are experimentally validated to reduce the computational burden and significantly increase the image quality under complex target motion dynamics.Time domain algorithms offer a non-approximated and general way for image reconstruction in both ISAR and MSAR. Previously, their use has been limited by the available computing power. In this thesis, a contrast optimization approach for time domain ISAR imaging is proposed. The algorithm is demonstrated to produce improved imaging performance under the most challenging motion compensation scenarios. The thesis also presents fast time domain algorithms for MSAR. Numerical simulations confirm that the proposed algorithms offer a reasonable compromise between computational speed and image quality metrics

Ground-based ISAR imaging of cooperative and non-cooperative sea vessels with 3-D rotational motion

Includes bibliographical references (leaves 175-188).Inverse Synthetic Aperture Radar (ISAR) images of sea vessels are a rich source of information for radar cross section (RCS) measurement and ship classification. However, ISAR imaging of sea vessels is a challenging task because the 3-D rotational motion of such vessels often gives rise to blurring. Blurry ISAR images are not desirable because they lead to inaccurate parameter estimation, which reduces the probability of correct classification. The objective of this thesis is to explain how 3-D rotational motion causes blurring in ISAR imagery and to develop effective techniques for imaging cooperative and non-cooperative sea vessels for RCS measurement and ship-classification purposes respectively. Much research has been done to investigate the effect of 3-D rotational motion on an ISAR image under the assumption that an object's axis of rotation is constant over the coherent processing interval (CPI). In this thesis, a new quaternion-based system model is proposed to characterise the amount of blurring in an ISAR image when a sea vessel possesses 3-D rotational motion over a CPI. Simulations were done to characterise the migration of a scatterer through Doppler cells due to the time-varying nature of the Doppler generating axis of rotation. Simulation results with realistic 3-D rotational motion show substantial blurring in the cross-range dimension of the resulting ISAR image, and this blurring is attributed to the time-varying nature of the angle of the Doppler generating axis of rotation and the object's rotation rate over the CPI