Although very accurate sea-ice motion can be extracted readily from high-resolution satellite images, such as synthetic aperture radar (SAR), there is a need for near-real-time daily covering Arctic-wide ice-motion datasets to serve the operational Ocean and Ice Forecasting centers as well as accessing the 3 decade long time series of passive microwave instruments for climate monitoring. However, the retrieval of such datasets from low-resolution satellite images is challenged by an increased quantization noise as the time span of displacement vectors is shortened. For accessing shorter time spans (less than 3 days) from the same instruments, we introduce a novel sea-ice motion tracking algorithm. It builds on the well known maximum cross-correlation (MCC) method but relies on a continuous optimization step for computing the components of the motion vector and is accordingly named continuous MCC (CMCC). The prime effect of adopting a continuous formulation is to remove the quantization noise, an artifact of the MCC. The dampening of this noise allows for computing spatially smooth 48 hour Arctic sea-ice motion vector fields from low-resolution (12.5 km) spaceborne imaging sensors. A processing chain was implemented and run for the Northern Hemisphere with several sensors (AMSR-E, SSM/I and ASCAT) for three Arctic winters (2006–2007, 2007–2008 and 2008–2009). Several well known large-scale circulation features are captured by those datasets as well as some more short-lived events such as the track of low-pressure systems travelling rapidly over sea ice and inducing strong deformations in the pack. Validation results are presented against in situ GPS trajectories collected during the International Polar Year. Error statistics are shown to be ranging between 2.5 and 4.5 km (standard deviation for both component of the vector) depending on the sensor being processed. The 37 GHz channels of the AMSR-E instrument give the best product. The operational low-resolution sea-ice drift product of the EUMETSAT Ocean and Sea Ice SAF (www.osi-saf.org) is based on the material presented in this manuscript.