Adaptive Neighborhood-Preserving Discriminant Projection Method for HRRP-Based Radar Target Recognition
Adaptive Neighborhood-Preserving Discriminant Projection Method for HRRP-Based Radar Target Recognition
复制标题
DOI：
10.1109/lawp.2014.2376591
复制
发表时间：
2015
影响因子：
4.2
通讯作者：
Huan-huan Zhang;D. Ding;Z. Fan;Rushan Chen
中科院分区：
文献类型：
--
作者：
Huan-huan Zhang;D. Ding;Z. Fan;Rushan Chen
提出了一种新的流形学习算法——自适应邻域保持判别投影法，用于高距离分辨率轮廓（HRRP）雷达目标识别的特征提取。该方法利用邻域保持投影（NPP）和自适应最大边际准则（AMMC）两种目标函数，既能在降维空间中保持原始数据的邻域结构，又具有良好的分类性能。将该方法应用于基于hrrp的雷达目标识别特征提取中。数值实验表明，该方法可以有效地降低HRRP的维数，并获得满意的识别率。
A new manifold learning algorithm named adaptive neighborhood preserving discriminant projection method is proposed for the feature extraction of high-range resolution profile (HRRP)-based radar target recognition. By utilizing the objective functions of both neighborhood-preserving projection (NPP) and adaptive maximum margin criterion (AMMC), the proposed method can not only preserve the neighborhood structure of original data in the dimensionality reduced space, but also exhibit good classification performance. The proposed method is applied to the feature extraction of HRRP-based radar target recognition. Numerical experiments show that the proposed method can effectively reduce the dimensionality of HRRP and give satisfactory recognition rate.