This paper introduces a binaural model for the localisation and tracking of a moving sound source's azimuth in the horizontal plane. The model uses a nonlinear state space representation of the sound source dynamics including the current position of the listener's head. The state is estimated via an unscented Kalman Filter by comparing the interaural level and time differences of the binaural signal with semi-analytically derived localisation cues from a spherical head model. The localisation performance of the model is evaluated in combination with two different head movement approaches based on open- and closed-loop control strategies. The results show that adaptive strategies outperform non-adaptive ones and are able to compensate systematic deviations between the spherical head model and human heads.