Classification of personnel targets by acoustic micro-Doppler signatures
Classification of personnel targets by acoustic micro-Doppler signatures
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DOI：
10.1049/iet-rsn.2011.0087
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发表时间：
2011-12-01
影响因子：
1.7
通讯作者：
Woodbridge, K.
中科院分区：
文献类型：
--
作者：
Balleri, A.;Chetty, K.;Woodbridge, K.
近年来，利用目标的微多普勒特征对目标进行分类引起了人们越来越大的兴趣。除了主要的整体平移外，目标还可能表现出额外的运动，例如振动和旋转，这在回波中产生包含独特目标特征的多普勒调制，因此可以用于执行目标识别。虽然利用微多普勒特征对目标进行分类已经被用于雷达系统的射频分类，但在声学方面的工作却少得多。在这项工作中，已经开发了一台工作在80 kHz的超声波雷达，以收集执行各种动作的人员目标的微多普勒信号。给出了一系列分类器和特征提取算法在区分这些微多普勒特征方面的性能。
Classification of targets using their micro-Doppler signatures has attracted a growing interest in recent years. In addition to their main bulk translation, targets may exhibit additional motions, such as vibrations and rotations, which generate Doppler modulations in the echo that contain unique target features and thus can be used to perform target recognition. Although target classification by micro-Doppler signatures has been exploited in the radio frequency regime for radar systems, much less work has been done in acoustic. In this work, an ultrasound radar operating at 80 kHz has been developed to gather micro-Doppler signatures of personnel targets performing various actions. The performance of a range of classifiers and feature extraction algorithms in distinguishing between these micro-Doppler signatures is presented.