This paper describes an application of the hierarchical mixture of experts algorithm to the registration of multiple cartographic models to noisy radar data According to the HME algorithm each model is represented by a set of maximum likelihood registration parameters together with a set of matching probabilities. This architecture can be viewed as providing simultaneous registration and hypothesis verification. The maps in the cartographic data-base compete to account for radar data through the imposed probability normalization. The resulting matching algorithm can be regarded as a generic tool for model retrieval from a data-base. Our evaluation on radar images illustrates some of the characteristics of the algorithm. Our main conclusions are that the method is both robust to added image noise and poor initialization.