Translational Motion Compensation and Micro-Doppler Feature Extraction of Ballistic Targets
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摘要: 针对传统逆合成孔径雷达(ISAR)成像中的平动补偿方法并不适用于弹道目标平动补偿的问题，该文提出了一种弹道目标平动补偿与微多普勒(m-D)特征提取方法。在分析有翼弹道目标未完成平动补偿时的m-D效应的基础上，首先采用形态学中的骨架提取方法抑制1维距离像旁瓣，再在快时间频率(距离)-慢时间平面上搜索分离各散射点的m-D特征曲线，然后对其进行经验模式分解(EMD)分解，利用分解结果中的趋势项分量完成目标回波的平动补偿，并通过分析EMD分解结果获得了目标的自旋频率、锥旋频率等特征信息。仿真实验验证了所提方法的有效性与鲁棒性。
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关键词:
- 目标识别 /
- 弹道目标 /
- 微多普勒(m-D) /
- 经验模式分解(EMD)
Abstract: The translational motion compensation methods for conventional Inverse Synthetic Aperture Radar (ISAR) are not suitable for ballistic targets. In the paper, an algorithm for ballistic targets translational motion compensation and micro-Doppler (m-D) feature extraction is proposed. Based on the analysis of m-D effect of ballistic targets with tails without translational motion compensation, the skeleton extraction algorithm in morphology image processing is firstly utilized to suppress the sidelobes of range profile, and then the m-D curves on the range-slowtime plane are separated. The Empirical-Mode Decomposition (EMD) algorithm is then utilized to obtain the translational motion component from the m-D curves for translational motion compensation. The micro-motion features of target such as spinning frequency and coning frequency are also obtained from the EMD results. Simulations are given to validate the effectiveness and robustness of the proposed algorithm. -
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