Modified nearest neighbor fuzzy classification algorithm for ship target recognition

Xiankang Liu, Baofa Wang, Xiaojian Xu, Jing Liang, J. Ren, C. Wei
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引用次数: 7

Abstract

Modified nearest neighbor fuzzy classification (MNNFC) algorithm is proposed for the character of ship target high resolution range profile (HRRP). Ship length, dispersant, symmetry and central moments features are some stable features for ship HRRP and extracted accurately. Modified nearest neighbor fuzzy classification algorithm is designed for different features to contribute their predominance because the significance and stability of each feature are different. And the membership degree of each feature is modified differently. Experimental results with the actual measured data of 10 ships show that the proposed algorithm is very useful in ship target classification.
舰船目标识别的改进最近邻模糊分类算法
针对舰船目标高分辨率距离像的特点,提出了改进的最近邻模糊分类算法(MNNFC)。船舶长度、分散剂、对称性和中心矩特征是舰船HRRP的稳定特征,提取准确。由于每个特征的显著性和稳定性不同,针对不同的特征设计了改进的最近邻模糊分类算法,以贡献其优势。并且对每个特征的隶属度进行不同的修改。10艘船舶实测数据的实验结果表明,该算法在舰船目标分类中是非常有效的。
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