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A method for estimating sound source distance in dynamic auditory ‘scenes’ using binaural data is presented. The technique requires little prior knowledge of the acoustic environment. It consists of feature extraction for two dynamic distance cues, motion parallax and acoustic τ, coupled with an inference framework for distance estimation. Sequential and non-sequential models are evaluated using simulated anechoic and reverberant spaces. Sequential approaches based on particle filtering more than halve the distance estimation error in all conditions relative to the non-sequential models. These results confirm the value of active behaviour and probabilistic reasoning in auditorily-inspired models of distance perception.