| Target micro-motion conveys features and information which are favorable for understanding synthetic aperture radar (SAR) images. However, micro-motion will result in defocusing and other unfavorable effects on target imagery, which can't be overcome by conventional SAR/ground moving target indication (SAR/GMTI). Therefore, this dissertation aims at micro-motion targets in SAR and detailedly investigates their detection, parameter estimation, and focusing approaches.Chapter 2 focuses on models of SAR micro-motion targets and backgrounds. We develop four types of micro-motion models including rotation, vibration, sinusoidal motion and rocking, as well as four types of scattering models including ideal point, distributed, localized and migratory scattering. We propose for blades two scattering center structures, and build a migratory scattering center model for parabolic-reflector antennas. Then background models and SAR echo simulation are studied. We derive a sufficient and necessary condition for applying 2D FFT methods to generate raw echos, and propose three kinds of algorithms for squint looking SAR with a constant velocity, constant acceleration and trajectory deviation, respectively, which enhance the simulation efficiency particularly for large backgrounds. Based on the resultant echoes, a novel approach to range Doppler SAR echo processing based on Legendre orthogonal polynomials is presented with smaller phase approximation errors and improved squint-looking applicability.Chapter 3 examines micro-motion effects on SAR and SAR/GMTI. We discover the sawtooth phenomenon between motion and phase orders, the range cell migration (RCM) sensitivity phenomenon incurred by minor-amplitude and fast-frequency micro-motion, and the angular-extent effect of micro-motion targets on images by the polar format algorithm. The sawtooth principle and the generalized paired echo principle are proposed. Then taking this as the rationale, we analyze in detail the effects of micro-motion types, parameters, target numbers and scattering on SAR algorithms and on the resolution limts. Eight typical kinds of features of SAR imagery are revealed, and we also conclude that micro-motion will considerably degrade the detecting performance for single-channel SAR, while has little influence on that of multi-channel SAR.Chapter 4 investigates clutter suppression and micro-motion target detection. A generalized likelihood ratio test (GLRT) detector are developed using SAR returns as opposite to images, the detecting performance are derived theoretically. Then for major-amplitude micro-motion, a special detection method is proposed which uses post-detection integration and discontinuous sine curve characteristics to obtain a high signal-to-noise ratio gain. Also for minor-amplitude micro-motion, an alternative based on target ghost images are proposed which uses the pulse repetition interval (PRI) transform to detect the ghost points and dispenses from the multiple period error. In light of limited single-channel performance, we also suggest another approach, based on dual-channel displaced phase center antenna (DPCA), for rejecting clutters and detecting micro-motion targets within the clutter spectra. These detection methods also have the capability of estimating micro-motion parameters.Chapter 5 concentrates on the refocusing of micro-motion targets, including translation compensation, RCM correction (RCMC), micro-motion signal separation/extraction, micro-Doppler unwrapping, Doppler centroid estimation and imaging. A norm on when RCM must be corrected is at first proposed. Then three RCMC algorithms are put forward based on bandwidth reduction, phase compensation and the Doppler successive Keystone transform, respectively. For range cells containing micro-motion targets, a Wigner-Hough-transform based method is proposed to compensate the translation, which uses characteristics of sinusoidal frequency-modulated (SFM) signals. In what follows, we use adaptive Chirplet decomposition to separate micro-motion returns from stationary ones, and consider the effect of Doppler aliasing on decomposition. For target azimuthal focusing, a sequence-interpolation based Doppler unwrapping approach is proposed for recovering the sinusoidal phase and time-frequency curve. Afterward the energy balancing method is used to estimate and compensate the Doppler centroid of SFM signals, based on which a micro-motion-eliminated autofocusing method and a micro-motion-utilized imageing method via inverse Radon are suggested respectively. We also conclude that, for anisotropic targets, their image by the inverse Radon transform only reflects the averaged scattering intense.Chapter 6 discusses the joint detection and imaging technique for SAR micro-motion targets. We at first propose a theoretical framework for joint detection and imaging of SAR target, including (1) forward problem modeling, (2) initial value estimation and prior information modeling, and (3) inverse problem solving. For (1), we prove that SAR target returns, with arbitrary scattering and/or motion, can be modeled by a Fredholm integral equation of the first kind. For our micro-motion targets, the equation is embodied by a hybrid motion-scattering model, i.e. the micro-motion/point-scattering model and the micro-motion/migratory-scattering model. For (2), we analyze radar cross section, range profiles, time-frequency distribution and 2D image characteristics of micro-targets, and reveal the bowknot-shaped feature of rotating parabolic antennas. Based on this, the initial value estimation method is given which can guarantee fast global convergence when solving the inverse problems. For (3), we propose that the inverse problem can be solved from the viewpoint of either the micro-motion target tomography or parameter estimation, and particular emphasis is placed on the latter one. A maximal likelihood estimation method for solving micro-motion target models is proposed to realize joint estimation of both motion and scattering parameters. This framework exploits prior information on target models and their characteristics to the utmost extent, and implicitly incorporates detection and imaging by introducing target model prior information, while also offers the potiential of incorporating platform motion compensation and jointly imaging both moving and stationary targets.To summarize, we have in this dissertation uncovered micro-motion target image characteristics and their formation mechanism, proposed a series of detection and imaging algorithms as well as a theoretical framework for joint detection and imaging. This dissertation has realized micro-motion target imaging and indication on SAR images. These research results bear certain significance for high-resolution and refined earth observation, precison bombing, fast SAR image interpretation and passive SAR jamming as well as its countermeasure.
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