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针对低信噪比条件下履带式车辆和轮式车辆的分类问题,提出一种基于微多普勒(Micro-Doppler,MD)特征和Duffing振子的低信噪比条件下车辆目标分类方法.首先,基于窄带雷达对两类车辆目标进行回波建模,分析了两类车辆目标微多普勒特征的主要差异,然后利用Duffing振子系统检测微弱信号的性能优势,在低信噪比条件下基于Duffing振子实现了两类车辆目标较高精度的分类,最后基于实测数据验证了所提方法的有效性.
Aiming at the classification problem of tracked vehicles and wheeled vehicles with low signal-to-noise ratio (SNR), a vehicle target classification method based on Micro-Doppler (MD) features and Duffing oscillator with low SNR is proposed. Based on the narrow-band radar, two types of vehicle targets are modeled as echoes, and the main differences between the two types of vehicle micro-Doppler characteristics are analyzed. Then, the performance of weak signals is detected by Duffing oscillator system. Based on the low SNR, Duffing oscillator realizes the classification of two types of vehicle targets with higher accuracy, and finally verifies the effectiveness of the proposed method based on the measured data.