We describe a sonar localisation system for autonomous mobile robot navigation in a known environment, which tries to extract as much information as possible from the sensors by building a detailed probabilistic model of each sonar event. It takes account of multiple hypotheses about the source of each signal and uses a probabilistic sensor fusion technique to merge the results into a single location update. The system is designed to run under our decentralised, highly parallel vehicle architecture, and we discuss some of the implementation techniques required to achieve this. The results of some initial simulations are presented.