Aircraft Target Classification Based on Correlation Features from Time-domain Echoes
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摘要: 该文研究了常规窄带雷达体制下利用时域回波调制周期的差异实现直升机、螺旋桨飞机和喷气式飞机3类飞机目标的分类问题。首先分析3类飞机时域回波调制周期的差异;然后针对3类飞机目标时域回波调制周期的不同,基于时域回波相关性提取了2维特征向量;最后基于仿真数据和实测数据,利用支持向量机(SupportVector Machine, SVM)分类器的分类结果证明了在脉冲重复频率较低时,多普勒谱有一定程度混叠的情况下,时域相关性特征仍能表现出相对较好的分类性能Abstract: This paper reports the classification of helicopters, propeller-driven aircraft, and turbojet based on differences in their time-domain modulation periods using a conventional radar system. First, we determine the modulation periods of their time-domain echoes. Then, based on the differences in the time-domain modulation periods, we propose a method for the extraction of time-domain correlation features. Finally, based on the simulated and measured data, via a support vector machine classifier, it is proved that the time-domain correlation features can yield the good classification performance, even with the relatively low pulse repetition frequency, which may induce the ambiguity in Doppler-frequency domain.
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Key words:
- Target classification /
- Feature extraction /
- Micro-Doppler effect /
- Time-domain echo
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