空间平滑局部保持投影用于ISAR目标识别  

ISAR Target Recognition using Spatially Smooth Locality Preserving Projections

作　　者：蔡洪[1] 何强[1] 韩壮志[1] 尚朝轩[1] 

机构地区：[1]军械工程学院光学与电子工程系,石家庄050003

出　　处：《光电工程》2009年第7期8-13,共6页Opto-Electronic Engineering

摘　　要：由于目标运动及其所处环境的复杂性,雷达目标数据之间往往呈现出局部的非线性,如果采用传统的线性子空间方法降维,必将会使雷达目标识别性能有所下降。基于以上原因,论文在详细分析ISAR二维像非线性流形结构特点的基础上,将流形学习方法中的空间平滑局部保持投影(Spatially Smooth Locality Preserving Projections,SSLPP)算法应用于ISAR二维像的特征提取和维数约简,并采用k近邻分类器对三类飞机目标进行了识别。与传统的子空间方法相比,SSLPP算法充分考虑了图像中各相邻像素之间的相关性,因而可获得更多的图像空间局部信息。仿真实验结果表明,与PCA、LDA、LPP等算法相比,该方法具有更好的识别性能。The relationship between different radar targets is often nonlinear due to the complexity of target movement and environments, so the recognition rate will decrease when traditional methods for linear dimensionality reduction are used. For this reason, the nonlinear manifold structure characteristics of ISAR 2D images were analyzed in detail, and then the Spatially Smooth Locality Preserving Projections （SSLPP） algorithm of manifold learning was used for feature extraction and dimensionality reduction. Moreover, three kinds of aircraft targets were classified by k-nearest neighbor classification. Compared with other traditional subspace methods, SSLPP algorithm can earn more local information of the image space by considering the spatial relationship between pixels in ISAR 2D image sufficiently. The simulated experimental results suggest that SSLPP algorithm has better classification performance than PCA. LDA and LPP algorithms in ISAR target recognition.

关 键 词：空间平滑局部保持投影 Laplacian平滑 ISAR二维像 目标识别 雷达成像 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]