A fundamental for an automated driving car is the awareness of all its surrounding road participants. Current approach to gather this awareness is to sense the environment by on-board sensors, like camera or radar. In the future Vehicle-to-X (V2X) might be able to improve the awareness, due to V2X's communication range superiority compared to the on-board sensors' range. Due to a limited amount of communication partners sharing their own ego states, current research focuses particularly on cooperative perception. This means sharing objects perceived by local on-board sensors of different partners via V2X. In this paper, temporal and spatial alignment of the shared objects is reviewed at track-level. State-of-the-art during the alignment procedure is the compensation of the sender motion in the object state and to perform the coordinate transformation of the object state using the predicted sender state. We propose to use the non-predicted sender state for the transformation and therefore to neglect the sender motion compensation. Finally, both methods are evaluated to figure out the best choice.