魏嘉琪^{1, 2},
张磊^{1, 2,,},
刘宏伟^{1, 2},
盛佳恋³
1.西安电子科技大学雷达信号处理国家重点实验室 西安 ??710071
2.西安电子科技大学信息感知技术协同创新中心 西安 ??710071
3.上海无线电设备研究所 上海 ??201109
基金项目:国家自然科学基金(61771372，61771367)，上海市自然科学基金(16ZR1434900)

详细信息

作者简介:魏嘉琪：女，1994年生，博士生，研究方向为ISAR成像
张磊：男，1984年生，副教授，研究方向为SAR/ISAR成像与运动补偿
刘宏伟：男，1971年生，教授，研究方向为宽带雷达信号处理
盛佳恋：女，1987年生，工程师，研究方向为SAR/ISAR成像，太赫兹雷达信号处理

通讯作者:张磊　leizhang@xidian.edu.cn

中图分类号:TN957.52

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被引次数:0

出版历程

收稿日期:2019-01-15
修回日期:2019-04-24
网络出版日期:2019-05-22
刊出日期:2019-12-01

A Novel Micro-motion Multi-target Wideband Resolution Algorithm Based on Curve Overlap Extrapolation

Jiaqi WEI^{1, 2},
Lei ZHANG^{1, 2,,},
Hongwei LIU^{1, 2},
Jialian SHENG³
1. National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
2. Collaborative Innovation Center of Information Sensing and Understanding at Xidian University, Xi’an 710071, China
3. Shanghai Radio Equipment Research Institute, Shanghai 201109, China
Funds:The National Natural Science Foundation of China (61771372, 61771367), The Natural Science Foundation of Shanghai (16ZR1434900)


摘要
摘要:针对传统的微多普勒特征提取技术难以解决多目标分辨和微动参数估计这一问题，该文针对进动多目标，提出一种曲线交叠外推的微动多目标宽带分辨算法。该算法以各个滤波数据点间的相对距离为准则，结合各曲线的历史斜率信息，对交叠点后的点迹进行外推估计，实现各个分量信号微动曲线的区分关联。在此基础上，通过分析各曲线的微动特性差异实现多目标分辨。仿真实验验证了所提算法的有效性和稳定性。
关键词:多目标分辨/
微动特征提取/
数据关联/
参数估计
Abstract:To solve the problem that the traditional micro-Doppler feature extraction technologies are generally hard to achieve resolution and parameter estimation of multi-target, a novel curve overlap extrapolation algorithm for wide-band resolution of micro-motion multi-target is proposed. According to the relative distance between filtering data points and the historical slope information of each curve, the point trace behind the overlapping location can be extrapolated to realize data association of micor-motion curve for each signal component. On this basis, the multi-target resolution can be realized by analyzing the difference of micor-motion characteristics between each curve. Extensive simulation experiments are provided to illustrate the effectiveness and robustnees of the proposed algorithm.
Key words:Multi-target resolution/
Micro-motion feature extraction/
Data association/
Parameter estimation



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