多频调频稀疏分解的微动目标参数估计方法

周叶剑; 张磊; 菅毛; 王虹现; 邢孟道

doi:10.11999/JEIT170163

多频调频稀疏分解的微动目标参数估计方法

doi: 10.11999/JEIT170163

基金项目:

国家自然科学基金(61301280, 61301293)

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- 文章访问数: 1271
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- 被引次数: 0
出版历程
- 收稿日期: 2017-02-27
- 修回日期: 2017-06-22
- 刊出日期: 2017-10-19

Micro-motion Estimation for Ballistic Targets with Multi-frequency Chirp Decomposition

Funds:

The National Natural Science Foundation of China (61301280, 61301293)

摘要

摘要: 精细化的回波微动调制分析是提取弹道目标运动几何特性的重要技术手段。该文提出一种多频点-调频傅里叶稀疏分解的微动估计方法来分析目标的时频特性。首先，该文介绍弹道目标进动回波微多普勒的一般表达；平动补偿后对回波局部分段并采用调频率傅里叶稀疏分解来估计局部微多普勒调频参数，有效利用了多频点回波的结构稀疏性，联合多频点稀疏分解提高算法稳健性；最后，拼接主频段信号各分段估计结果得到目标的微动曲线。电磁仿真数据验证了算法的有效性和稳健性，可用于弹道目标的微动分析、多目标识别等任务。
- 微动特性 /
- 调频傅里叶 /
- 时频分析 /
- 多频点信号 /
- 稀疏分解
Abstract: Accurate micro-motion characteristics analysis is an important technique to extract the geometrical characteristics of ballistic targets. In this paper, a multi-frequency Chirp sparse decomposition method for time- frequency analysis of micro-motion targets is proposed. First, the echo micro-Doppler expression of the equivalent scattering center model with the procession motion is deduced. After the translation compensation process, the multi-frequency echo are segmented and used to estimate the micro-motion characteristics with the Chirp sparse decomposition algorithm. While the sparseness of multi-frequency echo are effectively utilized, and the joint multi-frequency estimation improves the robustness of the algorithm. Finally, target,s micro-motion curve are obtained by stitching the segments estimation results. The validity and robustness of the algorithm are verified by electromagnetic simulation data and can be applied to time-frequency analysis and recognition of ballistic target.
- Micro-motions characteristics /
- Chirp Fourier /
- Time-frequency analysis /
- Multi-frequency /
- Sparse decomposition

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参考文献(24)

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