Two-dimensional forward-looking sonars such as Blueview or DIDSON are becoming a standard sensor in both remotely-operated and autonomous underwater vehicles. Registration of imagery obtained from this sensors is of great interest since it constitutes a key step in several applications like the generation of acoustic mosaics or the extraction of vehicle motion estimates from sonar imagery, specially on poor visibility conditions. However, the characteristics of these sonar images, such as low signal-to-noise ratio, low resolution and intensity alterations due to viewpoint changes pose a challenge to the traditional registration techniques applied on optical images. In this paper, the performance of popular registration methods commonly used in photomosaicing are evaluated on real sonar data, including feature-based methods and an area-based approach. Experiments are carried out on different environments, from man-made structured scenarios to more natural and featureless areas, and under challenging conditions such as viewpoint changes and the presence of different sonarspecific artifacts. After assessing the impact of all these factors on the different registration techniques, we show that Fourier-based registration method stands as the more robust option to register acoustic imagery.