###### Abstract
Since 2005 [16; 35; 36; 37; 38], several works have analyzed the application of DCA to ASAR data, thus demonstrating its potential for successfully retrieving the radial components of the sea surface currents. The computed Doppler Centroid (DC) shift complements the Normalized Radar Cross-Section (NRCS) measurements. Many examples of the application of the DCA methodology on C-band SAR data are relevant, especially over regions where strong currents occur, like in the Gulf Stream [14; 39] offshore of the USA coast, in the Agulhas Greater Current offshore of South Africa [36], and in the coastal area of the Normandy Gulf [16]. More recently, the DCA technique has been applied to areas with weaker currents than those mentioned above; in fact, some test sites in the Mediterranean Sea have been considered, e.g., the Gulf of Naples [15; 17; 40], the Northern Adriatic Sea [41] and the Black Sea [42]. Furthermore, the DCA technique has also been applied to inland waters, e.g., Lake Garda (the largest lake in Italy) [43]. Doppler and SAR backscatter information can also be complemented with wind information, for instance, provided by numerical models (e.g., ECMWF), to improve wind field estimation [13; 41; 42]. Concerning sea surface monitoring, the scientific literature provides a few examples of DCA applications to conventional spaceborne SAR data (large platform), mainly using C-band sensors [16; 35; 36; 37; 38]. However, DCA estimates are generally biased, leading to less accurate measurements (e.g., estimated in the order of 3-10 Hz for GAOFEN-3 SAR data) [33]. Consequently, the surface current velocity is also biased. To overcome this problem, some optimized filters have been designed to improve the precision of DC measurements at the Cramer-Rao bound, assuming the scene is quasi-stationary [33]. Newly updated equations for the calculation of the precision of DCA estimates have also recently been proposed in [44], which were verified with Monte Carlo simulations, providing a reference to develop future radar systems and identifying parameters design tailored to specific existence of seawater and ocean currents monitoring. Recently, a new family of SAR sensors has also been emerging. Among the others, in January 2018, ICEYE launched ICEYE-X1, Finland's first commercial satellite and proof-of-concept micro-satellite mission [45]. This micro-satellite constellation is equipped with more than 30 X-band sensor satellites that operate with different acquisition modes, guaranteeing a spatial resolution of some meters and a daily/sub-daily revisit time. In our work, we primarily focus on applying the DCA technique to ICEYE data and comparing its performance to previous generation C-band ASAR data, providing the readers with an assessment of the DC estimates precision, considering the operational parameters of the involved SAR systems. As said, the work of [PERSON] [31] derived some analytical expressions for the Doppler Centroid standard deviation (STD), considering different potential DC estimators. Since then, only a few other attempts have been made to characterize the precision of DCA estimates for stationary and non-stationary scenes. Considering the expected theoretical STD values of DCA for ENVISAT and ICEYE sensors, a cross-comparison analysis between the two SAR systems is provided here. The experimental results achieved by applying the DCA methodology to ASAR data are also presented. Since ASAR has broadly been used for surface current estimation, the relative results have been well assessed; indeed, it is used as a benchmark to provide valuable insights regarding DC estimation accuracy [32]. The remainder of the paper is organized as follows. Section 2 describes the set of SAR data used in our investigation. Section 3 briefly summarizes the theory behind the DCA technique for surface current velocity estimates. DCA is then applied to selected SAR scenes collected by ENVISAT and ICEYE, and the results of such a comparison analysis are presented in Section 4.