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。
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 micormotion characteristics between each curve.Extensive simulation experiments are provided to illustrate the effectiveness and robustnees of the proposed algorithm.
作者
魏嘉琪
张磊
刘宏伟
盛佳恋
WEI Jiaqi;ZHANG Lei;LIU Hongwei;SHENG Jialian(National Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China;Collaborative Innovation Center of Information Sensing and Understanding at Xidian University,Xi’an 710071,China;Shanghai Radio Equipment Research Institute,Shanghai 201109,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2019年第12期2889-2895,共7页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61771372,61771367)
上海市自然科学基金(16ZR1434900)~~
关键词
多目标分辨
微动特征提取
数据关联
参数估计
Multi-target resolution
Micro-motion feature extraction
Data association
Parameter estimation
