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Feature Extraction of Radar Range Profiles Based on Normalized Central Moments
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作者 傅雄军 高梅国 《Journal of Beijing Institute of Technology》 EI CAS 2004年第S1期17-20,共4页
The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as ... The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as feature vector for radar target recognition. The common feature extraction method for high resolution range profile obtained by using Fourier-modified direct Mellin transform is inefficient and unsatisfactory in recognition rate And. generally speaking, the automatic target recognition method based on inverse synthetic aperture radar 2-dimensional imaging is not competent for real time object identification task because it needs complicated motion compensation which is sometimes too difficult to carry out. While the method applied here is competent for real-time recognition because of its computational efficiency. The result of processing experimental data indicates that this method is good at recognition. 展开更多
关键词 radar range profile: automatic target recognition: normalized central moment: clustering analysis: nearest neighbor classifier
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