| 弹道目标平动补偿与微多普勒特征提取方法 |
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| 引用本文： | 罗迎,柏又青,张群,段艳丽,朱丰. 弹道目标平动补偿与微多普勒特征提取方法[J]. 电子与信息学报, 2012, 0(3): 602-608 |
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| 作者姓名： | 罗迎 柏又青 张群 段艳丽 朱丰 |
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| 作者单位： | 空军工程大学电讯工程学院;空军工程大学理学院;复旦大学波散射与遥感信息国家教育部重点实验室 |
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| 基金项目： | 国家自然科学基金(60971100,61172169);国家自然科学青年基金(61102109)资助课题 |
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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) |
Translational Motion Compensation and Micro-Doppler Feature Extraction of Ballistic Targets |
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| Luo Ying① Bai You-qing② Zhang Qun①③ Duan Yan-li① Zhu Feng. Translational Motion Compensation and Micro-Doppler Feature Extraction of Ballistic Targets[J]. Journal of Electronics & Information Technology, 2012, 0(3): 602-608 |
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| Authors: | Luo Ying① Bai You-qing② Zhang Qun①③ Duan Yan-li① Zhu Feng |
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| Affiliation: | Luo Ying① Bai You-qing② Zhang Qun①③ Duan Yan-li① Zhu Feng① ①(Telecommunication Engineering Institute,Air Force Engineering University,Xi’an 710077,China) ②(Science Institute,Air Force Engineering University,Xi’an 710051,China) ③(Key Laboratory of Wave Scattering and Remote Sensing Information(Ministry of Education), Fudan University,Shanghai 200433,China) |
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| 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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| Keywords: | Target recognition Ballistic targets micro-Doppler(m-D) Empirical-Mode Decomposition(EMD) |
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