机械与电子2017，Vol.35Issue(6)：12-17,6.
应用虚拟样本对SAR图像目标识别的研究
Research on SAR Image Target Recognition based on Virtual Sample
摘要
Abstract
Machine learning algorithm is one of the main methods of recognizing ground target SAR image;however, because of the difficulties of SAR image acquisition, it is impossible to guarantee a sufficient number of training samples during the machine learning algorithm.Thus, the recognition results will be affected.For the first time, this paper proposed the way to improve the recognition rate of SAR images by using virtual samples to expand the training set of SAR image target recognition.Through such methods as re-sampling algorithm, singular value reconstruction and contourlet reconstruction to generate virtual samples, this paper combined the training set with the original samples.An experiment was conducted on recognizing MSTAR data sets by means of training vector machine with SVM support.The results show that for different numbers of training samples, the recognition rate of SAR images can be improved by adding the virtual samples, especially in the case of small samples.This paper proves the effectiveness of using virtual sample in SAR image target recognition.When the number of samples is limited, adding virtual samples can significantly improve the performance of SAR image target recognition.关键词
SAR图像/机器学习/目标识别/虚拟样本Key words
SAR image/machine learning/object recognition/virtual sample分类
信息技术与安全科学引用本文复制引用
郑儒楠,刘文波..应用虚拟样本对SAR图像目标识别的研究[J].机械与电子,2017,35(6):12-17,6.基金项目
航空基金(20152052026) （20152052026）
国家自然科学基金(61471191) （61471191）
