Detection And Parameter Estimation Of Internal Wave By Space-borne Sar

Synthetic Aperture Radar(SAR)has the characteristic of all time,all weather condition and wide-area surveillance capability and it is becoming more and more widely used in the field of remote sensing.Internal Waves is a sort of wave motion occurred inside the fluids and ocean internal wave is the typical representation.Due to the large amplitude and great power the internal wave has,it can transport the energy and the nutrition.So it is of great value to pay more and more attention to the area of marine source exploitation,shipping dangerous avoidance and nation defence.With the SAR resolution increasing rapidly and the observing ability improving,SAR images contains much more information than before.Because the electromagnetic wave can not go through the water to sense the internal wave,sensors can only capture the scene of the sea surface for the research ers to deduce the real status inside the water.With to much clutter during the indirect procedure,there is lots of space for improving the accuracy and reducing the computation.In this dissertation,method of exploiting SAR images to locate the internal wave in it and research on the radar parameter's influence on image quality have been proposed.A statistical model parameter estimator based on the expectation maximum is also implied to fitting the real histogram.A series of concept of extracting the internal waves' s characteristical parameter is listed in the last chapter of this dissertation.The paper is organized as follows:Firstly,the model of internal wave's generation,propagating and dispersion is established and the hydrodynamic theory is introduced with its steady state solution.The widely used microwave scattering models is also introduced in this part for understanding the microwave-surface wave interaction and later simulation.Specified internal wave and imaging model is applied and t he concept of modulation depth is adopted to enhance the contrast of derived SAR image.The SAR parameter's influence on imaging quality and estimating accuracy is studied via picking up the extrema along the x direction and comparing that of different conditions.The aim of this analysis is seeking the best combination of observing sea surface;After that,a simple SAR preprocessing scheme is proposed to segment the ocean and land.A Markov random field based segmenting mean is introduced to enhance the existing stripe in SAR image for later internal wave locating from vast ocean based on Radon transform.As for the problem of heavy tailed or bi-/multi-modal characteristics of histogram,a solution related to general mixture model is derived.To solve the coupling of submodel weight and submodel parameters,the expectation maximum algorithm is adapted to estimate the parameter set.The accurately estimated statistical model is of great significance for despeckling,target dection and classification.To terminat e the iteration and evaluate the estimated result,the mean square error is employed,and iteration times is used to evaluate the computation.Combine the profile data and the known model of normalized radar cross section,the parameter in the model can be derived by curve fitting method.The empirical mode decomposition method is applied to analyse the component of the nonstationary signal and the component canbe used for parameter extraction.SAR interferometry method is also studied in this part for perceiving the sea surface motion by the relation between the phase difference and wave velocity.A framework based on the comparing and iterating is proposed for internal wave parameter estimation.