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A new ATR tool for coastal surveillance radars is proposed. This tool is based on new features from target range, azimuth profiles and an adaptive neuro-fuzzy classifier with linguistic hedges (ANFC-LH). The tests with real data show that the ANFC-LH used in our study has a better classification result in comparison with several other ensemble classification algorithms such as bagged decision trees and adaptive boosting. Moreover, it is shown that the proposed ATR tool with ANFC-LH has a better performance than that one given in a recent publication.
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