Characterizing submesoscale ocean processes requires high-resolution observations in both space O(1) km and time O(1) h. Resolving their velocity gradients requires velocity accuracies of O(1) cm s-1. In the present analysis, we utilize multiple mobile platforms, including Saildrones (SDs), to achieve high-resolution measurements of submesoscale features. We assess Saildrone acoustic Doppler current profiler (ADCP) measurements against shipboard ADCP data, both collected during the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE). The results show that the standard 5-min average Saildrone ADCP along-track velocity difference variability (3 cm s-1) is consistent with shipboard ADCP, considered in the present study as a reference. However, direct ADCP comparisons between a Saildrone and the R/V Oceanus give a small mean difference (∼1 cm s-1). The mean difference could stem from spatial inhomogeneities rather than surface waves, whose influence is expected to be negligible at most sampled depths. Based on 1-Hz Saildrone ADCP data, we found that averaging over 3 min of ADCP-derived currents (250 m in space) provides minimal unwanted signal. We investigate the uncertainty of submesoscale current gradients derived from Saildrone ADCP measurements and find that the velocity gradient at a 2-km scale can be obtained with a 0.1f uncertainty using four Saildrones. The methodologies we developed to ascertain the optimal averaging window are versatile and applicable to other uncrewed surface vehicles (USVs) or multiple-ship arrays.