Abstract:

Traditional methods of tactical intention analysis for sea targets, which are based on the information obtained from remote sensing interpretation, need plenty of expert knowledge to confirm the relationship of network nods between input target property and output intention. However, the fuzzy neural network only utilizes input and output samples in the network training process, reducing the requirement of expert knowledge. In tactical intention recognition for sea targets, the relationship between inputs and outputs is nonlinear so that the typical TakagiSugeno model cannot handle this situation. Thus, a fuzzy system model based on integrated neural networks is established, in which target property and the intention are used to train neural networks to obtain the degree of fuzzy membership and output functions of different intentions. Using that model, the tactical intention of sea targets is then recognized. Experimental results present high accuracy of tactical intention recognition and are consistent with the situation.