一种基于时频分析的窄带雷达飞机目标分类特征提取方法

摘要

针对低信噪比情况下窄带雷达目标分类问题,该文提出基于时频分析的窄带雷达飞机目标分类特征提取方法.该方法利用喷气式飞机、螺旋桨飞机和直升机3类目标调制周期的差异,提取时频谱域的熵值变化特性,并给出时频分析中窗函数长度的优化选择方法.基于仿真和实测数据的实验结果表明,该文方法可以在低信噪比情况下显著提升飞机目标正确分类概率.%A new feature extraction method based on time-frequency analysis is proposed for aircraft targets classification under low signal-to-noise ratio. This method uses the variances of time-domain modulation periods of jet aircraft, propeller aircraft and helicopter to extract the variation of entropy in the time-frequency domain and gives a way to select optimal window lengths. Experimental result based on simulated data and measured data demonstrates that the proposed method can significantly improve the classification probability of aircraft targets under low signal-to-noise ratio.