Research On Key Techniques Of Moving Target Detection With Distributed SAR

Synthetic Aperture Radar(SAR), which is a kind of newly arisen space-based radar system with all-weather and all-time capability after the World War II, receives much concern. The distributed SAR system with many advantages such as high spatial degrees of freedom, multi-task reuse and low system complexity etc. which is developed in recent years, becomes the research focus in many countries. Especially, the advantages of the distributed SAR system in ground moving target indication(GMTI) are increasingly obvious. However, with the fast development of the modern battlefield, some technique problems follow too. Among these problems, son-stationary clutter suppression problem, moving targets detection in non-homogenous clutter problem and moving target high-resolution 3D imaging problem are most urgent. Aming at these urgent problems, this paper,according to the features of the distributed SAR system configuration and the signal properties, proposes a series of effectual new GMTI technique using some advanced signal processing technology such as space-time joint processing, signal reconstruction and compressed sensing to fully use the distributed SAR system advantage and promote GMTI performance. The main research contents and innovations are as follows:(1) This paper establishes the signal model of the point target, clutter and moving target of the distributed SAR with non-uniform 3D configuration and analyzes the a series of effects of the targets motion on the echo signal spectrum theoretically; and points out the problem of the traditional GMTI technology based on the analysis of their principles.(2) Aiming at the problem that the traditional clutter suppression technology is not suitable to the practical configuration of the distributed SAR and can not suppress the non-stationary clutter related to range well, this paper proposes a signal reconstruction-3D time-space adaptive processing technology. This paper analyses the space-time feature of the echo signal, and points out the problem that the signal space sampling is not uniform combining with the practical configuration of the distributed SAR, and then reconstructs the non-uniform sampling signal to the uniform sampling signal, and derives the space-time spectrum feature of the non-stationary clutter, finally combining the system space freedom in elevation direction with 3D space-time joint processing technology to suppressing the non-stationary clutter effectively.(3) Aiming at the problem that the traditional GMTI technology requires the clutters around the cells under detection are independent identical distributed, this paper proposes phase compensation-maximum likelihood moving target detection method. This paper derives the phase differences produced by the clutter among the satellite platforms, and cancels the differences using phase compensation technology, then derives the phase differences produced by the moving targets among the satellite platforms, and extracts the motion information of the moving targets in the differences using maximum likelihood technology. This method does not require the clutter satisfying the independent identical distribution and caculating the clutter covariance matrix and its inverse matrix, but can detect the moving targets with small computational complexity in low SNR condition, and can promote the precision of the moving targets position and velocity detection.(4) Aiming at the problem that the present imaging technology is not able to abtain high-resolution moving targets 3D image. This paper proposes over-complete dictionary- basis pursuit moving target imaging method. This paper establishes the distributed SAR moving target echo discrete model, and according to the features of the system configuration and the distribution of the ground scattering point, then constructs 3D over-complete dictionary for the moving target echo signal sparse representation, and then derives the underdetermined system of equations to recovery the scattering coefficient from the sparse signal, and then according to the problem that the traditional method is not adaptive to the practical noise distribution, proposes the improved basis pursuit sparse signal recovery method to solve the underdetermined system of equations. Finally, the high-resolution moving targets 3D image is obtained, and the accurate 3D characterization of the moving targets is realized.The new technologies above are all propoesed according to the practical technology problem when the distributed SAR system carrying out GMTI task, and are obtained by the scientific derivation and correct experiment based on the understanding, analysis and using the feature of system configuration and echo signal. Therefore, this paper has practical application significance to the development of the distributed SAR system in GMTI. The thought of proposed signal processing technology, which can be extended to other signal processing application field general, has theoretical reference value.