On the basis of Hanada and Ejima's (2000) model, an algorithmic model was presented to explain psychophysical data of van den Berg and Beintema (2000) that are inconsistent with vector-subtractive compensation for the rotational flow. The earlier model was modified in order not to use vector-subtractive compensation for the rotational flow. The proposed model computes the center of flow first and then estimates self-rotation; finally, heading is recovered from the center of flow and the estimate of self-rotation. The model explains the data of van de Berg and Beintema (2000). A fusion model of rotation estimates from different sources (efferent signals, proprioceptive feedback, vestibular signals about eye and head rotation, and visual motion) was also presented.