In this paper, a concept for inertial position tracking of flow following sensor particles based on data fusion of inertial sensors is presented. The employed data fusion technique is quaternion based and uses an extended Kalman filter algorithm. A generalized sensor system kinematics has been developed to test the filter algorithm where two data conditions have been considered. Eventually, first simulation results are compared which shows the performance of the filter regarding sensor drift and noise.