# Phase Imbalance Analysis of GF-3 Along-Track InSAR Data for Ocean Current Measurement
## 4 Discussion  
In this paper, we firstly introduce and analyze the basic ocean current measurement principles by ATI mode. We deduce and analyze the theoretical formula of the cause of phase imbalance and then locate the source of the phase imbalance of GF-3 ATI mode using real data. Finally, according to the phase imbalance of the land scene in the same set of data, the phase imbalance of the ocean scene is calibrated, and the current velocity is measured. The current measured by the DCA method and HFSWR is used to verify the results measured by the ATI method. The contributions to the RMSE and the mean difference between the current measured by the ATI method and HFSWR are expected in many aspects. First of all, the phase imbalance error of the land scene cannot truly reflect the phase imbalance of the ocean scene. There is a time-varying phase imbalance in the azimuth due to satellite attitude and satellite velocity, which is not considered in the process of eliminating the phase imbalance between channels. Therefore, the calculated ocean surface radial velocity may not accurately reflect the Doppler velocity caused by ocean surface motion. Secondly, the accuracy of the retrieved current highly depends on the empirical model we used. For example, the CDOP model is obtained by using a three-layer neural network training the Doppler frequency shift of ASAR data and the wind retrieved by ASCAT; whether it is suitable for GF-3 data needs further verification. Thirdly, the accuracy of sea surface current velocity is sensitive to wind speed and wind direction error. However, the spatial resolution of ECMWF reanalysis data is lower than that of the GF-3 image, and they cannot match completely in time. In addition, the results also depend on the accuracy of current velocities measured by HFSWR. Therefore, it is hoped that we can obtain the in situ sea surface wind data and current velocity data to more accurately prove the accuracy of GF-3 data in ocean current inversion. According to our analysis of GF-3 ATI data, the current velocity measured by the ATI method based on dual channel data is basically consistent with that measured by the DCA method based on single-channel data. Furthermore, the ATI method needs dual receiving antennas or antenna arrays, while the DCA method only needs a single antenna, which is much simpler than the ATI method in hardware. Almost all SAR satellites have the ability of the DCA method for current measurement, which is more conducive to the operational measurement of current velocity. However, GF-3 ATI mode only has a 3.75 m along-track interferometric baseline, which is a short baseline. It can only show that the ATI method and DCA method have the same current measurement accuracy in the case of a short baseline. In addition, according to [PERSON]'s research on TerraSAR-X data [11], the short-baseline ATI method and DCA method have the same accuracy in general, but the  
Figure 17: Statistical chart of the error distribution of the ocean current obtained by the two methods. short-baseline ATI method has certain advantages compared with the DCA method in river measurement and ocean internal wave measurement. In addition, the ATI method can be used to measure the current velocity with high spatial resolution, which is much higher than the DCA method. In theory, the spatial resolution of the ATI method is consistent with that of SAR imaging; to improve the inversion accuracy, spatial average processing is needed, which reduces the spatial resolution of the current measurement by the ATI method. However, in order to obtain high-precision Doppler centroid frequency, the DCA method must carry out large-scale spatial averaging. In other words, the spatial resolution of the ATI method with a long along-track interferometric baseline is higher than that of the DCA method with the same accuracy. Due to the influence of image saturation distortion and different antenna beams, we can only rely on these two sets of existing data to get corresponding conclusions.