Research On The Features Of Vessel Target Based On Gaofen-3 Fully Polarimetric SAR Data

Synthetic Aperture Radar(SAR)is a microwave-based remote sensing system with strong penetration,unaffected by bad weather such as clouds,fog and haze,and is widely used for ocean monitoring.Compared with SAR images,polarimetric SAR(Pol SAR)data contains more backscattering information and phase information.The Gao Fen-3(GF-3)satellite is the first fully polarimetric civil microwave remote sensing satellite and has significant advantages in vessel target characterization due to its high data quality.Therefore,the characteristics studies on the vessel targets of GF-3 polarimetric SAR data are of great value and application prospects.Different types of vessels have different scattering characteristics and extracting effective features from them is the basis for refined interpretation of vessels.At present,the vessel structure is mainly refined by polarimetric multicomponent decomposition and feature extraction.However,the above two methods are not accurate enough to interpret the vessel superstructure.In addition,during the vessel refinement interpretation,the polarimetric SAR images of vessels are susceptible to ambiguity interference and energy offsets interference,thus making the vessel target features characterization not precise enough.At present,interference is mainly suppressed by differences in ship-sea scattering,and this method is suitable for azimuthal ambiguity interference.However,the suppression of energy offset interference is not effective.To address the above problems,this paper focuses on the scattering mechanism of vessel targets and their offset interference.The details of the work in this paper are as follows:1.The scattering characteristics of vessel targets and interference are analyzed on GF-3 fully polarimetric data.In this paper,the vessels in the cargo ports of non-military bases are mainly divided into three categories: bulk carriers,containers vessels and oil tankers.Using the polarization decomposition method and various polarization parameters to investigates scattering mechanism of the superstructure of vessels.Using the method of polarimetric feature extraction to analyze the scattering mechanism of fully polarimetric SAR data interference.2.To address the problem of offset interference on vessel targets under the GF-3 fully polarimetric SAR data,this paper proposes an interference feature filter to suppress it.Firstly,Yamaguchi decomposition and H/A/αdecomposition are combined to enhance the polarization characteristics of real targets and interference respectively.Secondly,using Rank-1 and generalized similarity parameters for the real vessel target to enhance the contrast between the ocean background and the real vessel targets.Finally,the interference is effectively eliminated by the proposed interference feature filter(IFF).This method can effectively suppress the energy scattering problem of fully polarimetric SAR data.3.To address the problem of the poor performance for vessel target interpretation by the polarization multi-component decomposition method under the GF-3 fully polarimetric SAR data,a refined feature characterization method of fully polarimetric SAR vessels for visual interpretation is proposed.Firstly,a scattering model-based decomposition method is used to extract vessel target features.Then,a nine-classification plane was obtained with non-fixed threshold division,which reduces the category randomness generated by noise at the threshold boundary by hard thresholding.Secondly,the improved GSPWishart distance algorithm is used to highlight double bounce scattering and mixed scattering mechanisms by iterative clustering for the classified region.It is demonstrated that the method can better match the scattering types of the vessels in the and assist in improving the efficiency of visual interpretation.