Target classification by using pattern features extracted from bispectrum-based radar Doppler signatures
Target classification by using pattern features extracted from bispectrum-based radar Doppler signatures
复制标题
使用从基于双谱的雷达多普勒特征提取的模式特征进行目标分类
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
A. Totsky
中科院分区：
文献类型：
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作者：
P. Molchanov;J. Astola;K. Egiazarian;A. Totsky
本文提出了一种新的基于双倒谱的雷达运动目标分类方法。在我们的研究中，模式特征提取的短时后向散射双谱估计使用地面监视多普勒雷达测量。采用高斯混合模型（GMM）和最大似然（ML）决策方法研究分类器性能。我们的实验结果表明，是非常可行的识别三类人（单人，两人和三人）在植被杂波环境中使用建议的双谱为基础的战略。基于双谱的特征提取提供了对运动雷达目标分类的额外洞察，其上级于通常利用基于能量的特征。
In this paper, a novel bicepstrum-based approach is proposed for moving radar target classification. In our study, pattern features are extracted from short-time backscattering bispectrum estimates measured by using ground surveillance Doppler radar. Classifier performance is studied by Gaussian mixture model (GMM) and maximum likelihood (ML) making decision method. Our experimental results show that is quite feasible to recognize three classes of humans (single, two and three humans) moving in vegetation clutter environment by using proposed bispectrum-based strategy. Bispectrum-based features extraction provides additional insight into moving radar target classification that is superior to common utilizing energy-based features.