Studies On Information Processing Technique Of Polarimetric SAR

Compared with the single polarized SAR (synthetic aperture radar), polarimetric SAR (Pol-SAR) holds more information of targets, which is one of the most important aspects of the microwave imaging research and development. Polarimetry properties of electromagnetic (EM) waves are sensitive to the scatters permittivity, physical trait, size, orientation and so on. The polarimetric scattering matrix, which describes the backscattering properties of targets completely, can be measured by transmitting and receiving different polarized signals.The Pol-SAR processing is based on information extraction of targets, which involves both physics and mathematics, i.e. not only reflects its scattering properties, but achieves it in mathematics. In this dissertation, based on the extraction of meaningful polarization information, the polarimetric speckle reduction, polarimetric contrast enhancement, polarimetric classification and ship detection in polarimetric SAR images are systemically studied. During the study, some new concepts and methods are introduced, which are supported by the application to measured Pol-SAR data. The innovations of this dissertation are as follows:1) A simplified schem is proposed to reduce the complexity of scattering-model-based speckle filtering.2) Extend the expression of polarimetric correlation coefficient to help distinguishing targets. In addition, introduce the quantized parameters of polarimetric signature so as to show the differentiae in quantity in co-polar power, cross-polar power and shapes of polarization signatures among targets.3) Define a new parameter of difference degree between targets, which can be used for express the difference between both coherent and distributed scatters. Besides, the difference degree is applied to polarimetric classification. A new unsupervised iterative classification method based on difference degree is proposed, which is better in keeping edges, more robust and simpler to programming than Wishart classifier.4) Develop a new method to sample ships adaptively, which is used for polarimetric contrast enhancement. The adaptive method is more robust than choosing ships samples manually. Our research shows that the enhanced degree is not very notable between the similar scattering targets using polarimetric contrast enhancement. We also verify the way is feasible to enhance the contrast between ships and clutter by algebraic operation to different polarimetric channels. 5) Use the polarimetric classification into ship detection. We propose a new ship detection method base on feature vector, which can detect ships form the sea, island and other man-made objects. At the same time, we propose the method of ship discrimination based on the co-pol phase difference. The application to AIRSAR and SIR-C data shows it is simple and effective.