This thesis is concerned with the navigation problem for autonomous underwater vehicles operating in artificial structured environments like harbours, marinas, marine platforms and other similar scenarios, Obtaining an accurate position in such scenarios would notably increase the capabilities of underwater vehicles and open the door to real autonomous operation. Maintenance, inspection and surveillance of marine installations are only a few examples of possible applications. The principal contributions of this thesis consist of the development of different localization systems for those situations in which an a priori map of the environment is available but, in particular, in the development of a novel solution to the Simultaneous Localization and Mapping (SLAM) problem. This solution pursues the objective of providing an autonomous vehicle with the ability to build a map within an unknown environment while, at the same time, using this same map to keep track of its current position. A mechanical scanning imaging sonar has been chosen as the principal sensor for this work because of its relative low cost and its capacity to produce a rich representation of the environment. On the other hand, the particularities of its operation and, especially, its low scanning rate, have presented many challenges during the development of this proposed localization strategies. The solutions adopted to address these problems constitute another contribution in this thesis. The development of underwater vehicles and their use as experimental platforms is another important aspect of the research work presented here. Experiments carried out in both laboratory and real application environments have provided the different datasets necessary for the testing and evaluation of the different localization approaches.