Study On The Imaging Theory And Method Of Multi-channel SAR

In recent years, multi-channel SAR which is represented by multi-polarimetric and multi-antenna has become an advanced issue in the area of synthetic aperture radar. Multi-polarimetric information improves the completeness of the description of target scattering characteristics. Multi-antenna allows SAR observing the scene from different viewing angles, enlarges its information source and greatly expands the application range of SAR. In order to improve the battlefield intelligence reconnaissance and processing capability of multi-channel SAR, this thesis studies the imaging and post-processing of it. The research achievements could expand the appliations fields of SAR in super resolution imaging, forward-looking imaging and moving target imaging.Chapter 1 illustrates the background and significance of this research subject, summarizes the research status of polarimetric SAR(Pol SAR) speckle filtering, Pol SAR super-resolution imaging, forward-looking SAR imaging, multi-channel SAR-GMTI, analyzes the disadvantages of current research on these areas and finally gives a brief introduction of the major works in this thesis.Chapter 2 studies the Pol SAR speckle filtering techniques. Firstly, formation mechanism and statistical properties of speckle noise are reviewed and several classical Pol SAR speckle filtering algorithms are introduced. As a result, it is found that speckle filtering algorithms based on statistical correlation between polarimetric channels usually tend to negect the filtering of non-diagonal elements of polarimetric matrix and the filtered data will suffer from crosstalk, making the polarimetric information changed. However, for widely explored refined Lee filtering algorithm and IDAN filtering algorithm, the similarity judgement of polarimetirc scattering characteristics either simply accomplished by 8 edge-aligned windows or using merely amplitude information, but not the full information carried out by polarimetric matrix. To overcome these disadvantages, a novel Pol SAR speckle filtering algorithm —— PDAN which is based on mean shift is proposed. This algorithm utilizes joint filtering in spatial domain and range domain, sufficiently exploits the full information involved in polarimetric matrix, and satisfies principle of Pol SAR speckle filtering. Experimental results based on L-band E-SAR data of German DLR and X-band Pol SAR data of CETC 38 research institution illustrate the excellent performance of the proposed algorithm.Focusing on “antinoise performance improvement” and “super-resolving imaging”, Chapter 3 sutdies Pol SAR super-resolving imaging method. Firstly, a novel imaging framework for stepped frequency SAR is proposed. In this framework, the influence of clutter and noise can be much reduced. Then, based on compressive sensing theory and non-quadratic optimization technique, an iterative super-resolving imaging algorithm named IFCS is proposed. Imaging results based on simulation data illustrates the better performance of IFCS in antinoise and super-resolving. Then, X band stepped frequency rail SAR experiment system is set up and imaging experiment is carried out based on it. Imaging results based on measured data further demonstrate the efficiency of proposed algorithm. For corner reflectors, the images obtained by IFCS have cleaner background and lower sidelobe. For the military truck which has complex structures, besides lower sidelobe, more details are captured in the image by IFCS.Chapter 4 presents a thorough research on high velocity multi-channel forward-looking SAR imaging algorithms. Firstly, aiming at the problem that existing imaging algorithms of multi-channel forward-looking SAR are all based on the situation that the platform is moving in low velocity, the signal model of high velocity multi-channel forward-looking SAR is established. Based on it, the DBS and RD imaging algorithms suitable for high velocity multi-channel forward-looking SAR are proposed, and the motion compensation of high velocity platform is solved. Then, in order to overcome the poor azimuth resolution induced by limited azimuth aperture length, compressive sensing theory is applied to multi-channel forward-looking SAR, and two super-resolution imaging algorithms suitable for high velocity multi-channel forward-looking SAR are proposed. Among them, the two dimensional super-resolution imaging algorithm has super-resolving ability no less than 5 times, whereas the two-dimensional mesh involved in it making it computationally expensive. By contrast, the computational complexity is much lower for the azimuth super-resolving algorithm, while the resolution and accuracy of imaging slightly reduces. Imaging simulations based on image data from the Mini SAR system demonstrate the effectiveness of the azimuth super-resolving algorithm.Chapter 5 studies multi-channel SAR-GMTI techniques. Firstly, the echo model of moving target in SAR system in established and the imaging result is analysed utilizing theory derivation and computer simulation. Based on these work, the echo of the moving target in different channels are analyzed and the signal model of the multi-channel SAR-GMTI is extablished. Then, 3 classical multi-channel SAR-GMTI processing algorithm, DPCA, ATI and STAP are reviewed which pave the way for real 7 channel SAR-GMTI data processing. This system is the first 7 channel SAR-GMTI system inland. However, the missed inertia navigation information raises the challenge for data processing. In order to overcome this negative effect, researches on autofocus, channel balancing and reduced rank STAP are carried out. Finally, the clutter is filtered and the moving targets are detected. This is the first time 7 channel SAR-GMTI data were processed in China, thus having special significance.Chapter 6 summarizes the major work and the innovations of this thesis, and discusses the future work.