Study On Key Techniques Of SAR-GMTI For Multi-channel Radar System

Synthetic aperture radar (SAR) is a great achievement of modern radar. Like various optical sensors, SAR can provide a two-dimensional image of a scene with good spatial resolution and high precision of radiation measurement, with the advantages of all-weather working, and long-range surveillance. Therefore, SAR is of great value for both civilian and military applications. Traditional SAR radars simply take the"picture"of a stationary scene. If moving targets exist, however, the SAR image will become blurred. A moving target with radial velocity on the SAR image will exhibit displaced from its true position, and the motion in the azimuth direction will cause its image to be dispersed along azimuth. In practical applications, especially in military application, it is always expected to achieve ground moving target indication (GMTI) by using SAR sensors and to relocate ground moving targets on the SAR image of the scene. This technique is called SAR-GMTI. Since along-track multi-channel SAR can provide more degrees of freedom than single channel one, along-track multi-channel SAR, as the optimal system geometry, provides the powerful ability to suppress the land/sea clutter for target detection and parameter estimation. Thus it has been used extensively for air-to-ground surveillance and reconnaissance purposes.In recent years, many countries around the world have been making great effort to develop spaceborne/airborne radar for GMTI based on multi-channel SAR, explore new SAR-GMTI technologies and design highly efficient detection and location algorithms. Based on the extensive investigation of the airborne SAR-GMTI, this thesis presents SAR-GMTI theory and investigates moving target detection, parameter estimation and imaging approaches. We deal mainly with channel equalization, clutter suppression and moving parameter estimation in SAR-GMTI for along-track side-looking array radar.The main work of the thesis is summarized as follows:1. To deal with channel equalization, an adaptive blind channel equalization approach, which can mitigate the influence of strong target signals or interferences contamination, is proposed for multi-channel SAR-GMTI system. Based on the obtained SAR images, firstly, the method chooses pixel data vectors with relatively strong power and enables these vectors modulus-normalized. Secondly, these modulus-normalized vectors are used to construct the covariance matrix and then the eigen-decomposition of the covariance matrix is performed. The eigenvector associated with the largest eigenvalue contains the information regarding the channel imbalance. Finally, the channel imbalance is corrected by dividing each element of the original pixel data vector by the corresponding element of the eigenvector associated with the maximum eigenvalue. The validity and robustness of the proposed approach are confirmed by theoretical analysis and the real data processing.2. For the multi-channel SAR-GMTI system, the presence of large image coregistration errors will have serious influence on the performance of the clutter suppression and the precision of parameter estimation. To deal with the problem, a new adaptive approach based on joint correlation steering vector for moving target detection is proposed. The method, in general, can increase the degrees of freedom of adaptive processing, and as a result, its performance of clutter suppression is greatly improved. It has good robustness to image coregistration errors, and can provide accurate estimates of the radial velocities of ground moving targets. The validity and superiority of this method are verified by the simulated data.3. A robust eigen-subspace projection approach to clutter suppression is proposed for a multi-channel SAR system. In an ideal environment, the conventional eigen-subspace projection method can offer a perfect performance of clutter suppression. In practice, however, it suffers seriously from strong target signals or interferences contamination. To deal with this problem, a new eigen-subspace projection method is presented. Performance analysis shows that the method is robust to strong target signals or interferences contamination. Simulation results and the real data processing confirm the validity of the method.4. An adaptive beamforming method based on modulus-normalized vector is proposed. It uses the suboptimal weight vector to suppress clutter and then searches target radial velocity at the detected position of the target using the optimal weight vector. The radial velocity can be estimated according to the criterion of the maximum signal-to-clutter plus noise ratio output. Finally, the moving target can be correctly relocated on the SAR image according to the estimated radial velocity. This method can mitigate the influence of target signals or interferences contamination. Simulation results and the airborne radar real data processing confirm the validity and robustness of the proposed method.