The Arctic is an important region containing large amount of unused potential. It is expected that a large amount of the worlds undiscovered oil and gas resources are located here, and the shortest route between northern Europe and eastern Asia called the Northern Sea Route (NSR) goes through the area. However, the presence of large amount of ice in the Arctic makes it a harsh and difficult environment to operate in.In order to operate in the areas where ice is present, some sort of ice management system is required. Ice management can be described as the objective to minimize the effect of ice features on floating vessels. Operations including oil and gas exploration and exploitation is complex and require predictability with respect to drifting ice in order to be able to disconnect in time. This has lead to the need of ice intelligence which is able to predict the ice movement.This study has look upon the problem of estimating ice drift velocity which is a critical parameter in an ice intelligence system. The estimation scheme used in this paper is based on ice concentration measurements and uses the measurements in combination with a numerical model to estimate the ice drift velocity. The results from the study shows that it is possible to estimate both ice drift velocity and ice concentration based on a limited amount of measurements.