Analysis Of Influence Factors And Simulation Research On SAR Image

Synthetic aperture radar (SAR) imagery has found important applications due to its clear advantages over optical satellite imagery one of them being able to operate in various weather conditions.Statistical characteristics are very useful in analyzing remote sensing images. At first, six kinds of image's major statistical characteristics based on different mechanism are introduced: co-occurrence matrix, the fractal characteristics, gray difference, histogram, auto-correlation function and the TAMURA. Then, the correlativity between band (or polarization and the angle of incidence) the statistical characteristics of the SAR image are researched. Experiments show that, under the changing of SAR system parameters, the sensitivities of different statistical characteristics are different. It means we should select and extract different image features in different tasks. Furthermore, the information fusion method, to take full advantage of the multi-parameter SAR image's characteristics, will achieve good performance.To simulate SAR image, a new simulation method of information fusion has been showed in this paper. It can make an expected image of a different radar parameter by using any known SAR image and its geographic information (the DEM data of the target region). Experimental results show that this method of SAR image simulation is very fast, and the scattering properties of target region have also been better realized.Finally, a method using multi-channel information fusion technology has been proposed to improve the recognition ability and classification accuracy of SAR image. SAR image characteristics and radar system parameters are related. By using the complementary information of multiple images, the objects in shadow can be identified correctly. It is a difficult problem in the single parameter SAR image analysis.The paper will be helpful in further analysis of the statistical characteristics of SAR images, the rule of structural characteristics variation of the SAR image. And the results provide a method and a useful experimental platform for the research of scene matching, scene navigability analysis based on SAR image.