Efficient processing of Top-K queries has always been a significant technique in the interactive environment involving massive amounts of data. With the emerging of imprecise data, the management of them has gradually raised people's attention. In contrast with traditional Top-K query, Top-K query on uncertain data presents different features both in semantics and computation. On the basis of prevailing uncertain data model and possible world semantic model, researchers have already studied multiple sound semantics and efficient approaches. This survey describes and classifies Top-K processing techniques on uncertain data including semantics, rank criteria, algorithms and implementation levels, and so on. Finally, the challenges and future research trends in processing of Top-K queries on uncertain data are predicated.