Research On Azimuth Ambiguity Suppression Algorithm For Nearshore Current Retrieval Based On ATI-SAR

Ocean current,one of the common motion forms of sea water,is an important parameter affecting and regulating global climate change.Compared with in situ observation and high frequency ground wave radar measurement,along-track interferometric(ATI)synthetic aperture radar(SAR)has the advantages of high resolution,wide width,low cost and not being affected by weather.Therefore,ATI-SAR system is used as a powerful remote sensing tool in the measurement of sea surface currents.However,in coastal waters,azimuth ambiguity often appears in SAR images due to under-sampling of signals,which has a great impact on the accuracy of current measurement.In this paper,the error formula of current measurement with azimuth ambiguity is derived,and the influence of radar system parameters,ambiguous signal ratio and wind speed on the error of current measurement is simulated and analyzed.In order to improve the current line-of-sight(LOS)accuracy of ATI-SAR,azimuth ambiguity suppression is needed.In this paper,the azimuth ambiguity suppression method and relative weighted method are proposed respectively in the SAR image domain.The baseline-platform velocity ratio(BPSR)estimation method based on eigenvalue spectral entropy analysis(EVSE)in SAR Doppler domain.The relative weighted azimuthal ambiguity suppression method proposed in this paper is based on the ratio of the average scattering intensity of SAR image to the power value of each pixel(the ratio is less than 1).The ratio is used as the weighted coefficient of the interference pair for ambiguity suppression.This method is suitable for coastal waters where the contrast between land and sea is small and the sum of artificial objects is large.In this paper,another BPSR estimation method based on EVSE analysis is proposed,which is based on the improvement of characteristic spectrum entropy analysis method.These improvements include considering the influence of satellite orbit and inaccurate baseline,measuring the scene inhomogeneity,correcting the phase fluctuation of coherent inference(CPF)and the phase variability derived from interference(IPV);the last two variables are closely related to the determination of EVSE thresholds.In addition,the method achieves BPSR estimation.Existing methods are usually based on ideal case assumptions,while the method presented in this paper is targeted at the actual operating environment and takes into account the accuracy of BPSR,which is suitable for more ATI-SAR systems.This thesis of pixel eliminating method put forward by the predecessors,adaptive multiple methods and characteristics of spectral entropy analysis method,this paper puts forward relative weighting method and based on the analysis of the EVSE,BPSR estimation methods were tested and compared,this paper puts forward the improved method is applied to coastal areas to the surface of the velocity of simulation data,the root mean square error(RMSE)is less than0.05 m/s.The other advantages of the algorithm are adaptability,robustness and less user input requirements.Most importantly,compared with other methods,the improved method proposed in this paper can be used in practical applications.