Underwater target recognition system based on Case-Based Reasoning

Case-based reasoning(CBR) is a recent approach to problem solving and learning. Originating in the US, the basic idea and underlying theories have spread to other continents. In this paper, A underwater target recognition system based on CBR is designed. A naval vessel¿s noise is a initial problem definition, its type is this problem solution, the feature vector of naval vessel¿s noise and its type is regarded as a case. Applying a stepwise approach to retrieve a best match case from previous cases, and then the best match case is used to identify the type of underwater target. Experiment results have showed that the system has better adaptability and more higher correct recognition probability.