Research On Sea Surface Property And Ship Target Detection Method In Airborne Circular Scanning SAR

Sea surveillance is always the emphasis and hot issue in military and civil application,airborne circular scanning synthetic aperture radar(SAR)can scan 360 degree and realize the wide surveillance of sea surface.Sea surface is motional and possesses space-varying and time-varying feature so that the scatting property of sea surface is complexity.The strong clutter exists,and especially in the high sea state,the distribution tail of sea clutter will severe.Therefore,it is very significant to study statistical distribution model of sea clutter,which will affect the target detection performance.Due to the complexity of sea clutter,the ship monitoring in the sea clutter is always the difficulty.The dissertation mainly studies the sea surface characteristics and the ship target detection in airborne circular scanning SAR,and the main contents include as follows:1? The estimation method of the sea surface current is studied.Circular scanning SAR is a novel imaging mode wherein the radar antenna scans 360 degree along the platform flight direction,providing us with a potentially effective technique to estimate the sea surface current velocity.After compensating the airborne platform motion,the motion of sea surface produces the Doppler centroid shift,and the Doppler centroid shift is different for different scan angels of airborne circular scanning SAR.Therefore,in this dissertation,we estimate the sea surface current velocity utilizing the Doppler centroid shifts of different scan angles over 360 degrees.In the proposed method,the Doppler centroid shifts of the sea clutter at different scan angles are first extracted,and the compensation error caused by the azimuth pointing is considered.Finally,the least squares technique is applied to estimate the along-track velocity component and the cross-track velocity component of the sea surface current.In experimental analysis,the effectiveness and availability of the proposed method is verified by the real data recorded by an airborne circular scanning SAR system.2? The applicability of statistical distribution model for the real sea clutter is analyzed.The theoretical statistical model of sea clutter is the significant property and the statistical model of sea clutter has attracted much attention to design the detector well in recent years.Circular scanning SAR can scan the sea surface over 360 degree,and the dissertation analyzes the validity of different distribution models of sea clutter for real data from different scan angles of airborne circular scanning SAR the in medium grazing angle.The distribution parameters of different statistical distribution models are estimated by the method of logarithmic cumulants(Mo LC)based on Mellin transform uniformly.The dissertation applies the fitting result between the histogram of real data and the amplitude probability density function(PDF)of empirical statistical distribution models and the goodness-of-fit(Go F)test to verify the fitting degree for real data of the sea clutter.3? The ship target detection is the key importance for the maritime surveillance,and the dissertation studies the detection method of extended ship target in airborne circular scanning SAR.If the sea clutter is contaminated by the outliers containing ship targets or interferences,etc.,the tail of the estimated distribution model for sea clutter is severe so that the detection performance will deteriorate.Aiming at this question,the dissertation develops the censoring method of the outlier.The algorithm mainly considers the statistical similarity of sea clutter from adjacent scan angle of circular scanning SAR and proposes the iterative censoring method of the outlier by the fuzzy statistical theory and the space property of target so that the pure sea clutter is obtained.Meanwhile,considering the small outliers,we propose the histogram detection method based on the fuzzy statistical theory.As the intensity of real ship target is fluctuant,the detected ship may be mistook as several targets and thus the target clustering is an imperative procedure.Meanwhile,the false targets are rejected by the prior size of the ship target.The effectiveness and availability of the proposed detection method is verified by the real data.4? The ship detection in polarimetric synthetic aperture radar(Pol SAR)mode is a hot topic in recent years,because of the diversity of polarimetric scattering mechanisms.To improve the detection performance of low signal-to-clutter ratio(SCR)ship targets,this dissertation mainly develops the ship detection method based on the contrast enhancement utilizing the polarimetric scattering difference.The algorithm first enhances the target signal utilizing the scattering difference of the polarimetric coherency matrix between ship targets and sea clutter,and then a simple threshold is applied to distinguish the ship targets from the sea clutter.Finally,we use real fully polarization datasets to evaluate the effectiveness of the proposed detection method,and compared with other detection methods,the experimental results show that the proposed method can remarkably improve the detection performance of ship targets and be applied in practice.