基于同步提取变换和脊线检测的空间锥体目标微多普勒特征提取方法

doi:10.12305/j.issn.1001-506X.2024.11.10

摘要/Abstract

摘要：

针对空间锥体目标微多普勒(micro-Doppler, m-D)提取时在m-D曲线交叉处易出现跟踪错误的问题, 提出一种基于同步提取变换(synchro-extracting transform, SET)和脊线检测的m-D特征提取方法。首先, 该方法利用SET技术得到能量分布更加集中的时频像, 并使用Hough变换提取锥体顶部产生的正弦m-D曲线; 之后基于CLEAN思想, 将提取到的顶部m-D曲线从时频像中消除; 最后利用基于改进疯爬算法和卡尔曼滤波的脊线检测算法提取锥体底部产生的非正弦m-D曲线。仿真结果表明, 该方法可以避免m-D曲线交叉处的跟踪错误问题, 正确提取m-D特征。

关键词: 同步提取变换, 空间锥体目标, 微多普勒, Hough变换

Abstract:

To solve the problem of the tracking mistakes at curve intersections of micro-Doppler (m-D) in m-D extraction of the space coning target, an m-D feature extraction method based on synchro-extracting transform (SET) and ridge detection is proposed. Firstly, the algorithm obtains the energy-concentrated time-frequency image through SET technology. Secondly, the sinusoidal m-D curve generated at the top of the coning target can be extracted by the Hough transform. Then, the extracted top m-D curve is subtracted from the time-frequency image based on the CLEAN idea. Finally, the non-sinusoidal m-D curve at the bottom of the coning target can be extracted by the ridge detection algorithm based on the improved crazy climber algorithm and Kalman filter. Simulation results show that the proposed algorithm can avoid the problem of tracking mistakes at the intersection of m-D curves, and then accurately extract the m-D features.

Key words: synchro-extracting transform (SET), space coning target, micro-Doppler (m-D), Hough transform

中图分类号:

TN957

王磊, 苏倩, 韦高, 李建周. 基于同步提取变换和脊线检测的空间锥体目标微多普勒特征提取方法[J]. 系统工程与电子技术, 2024, 46(11): 3684-3689.

Lei WANG, Qian SU, Gao WEI, Jianzhou LI. Micro-Doppler feature extraction method for space coningtarget based on synchro-extracting transform and ridge detection[J]. Systems Engineering and Electronics, 2024, 46(11): 3684-3689.

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参考文献 17

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参数	取值	参数	取值
雷达载频/GHz	10	进动角/(°)	10
脉冲重复频率/Hz	1 000	进动频率/Hz	2
锥体高度/m	3	视向角/(°)	30
质心高度/m	0.75	自旋频率/Hz	2
底面半径/m	0.75	积累时间/s	1

参数	真实值	估计值
A/Hz	-156.85	-156.57
ω_c/(rad/s)	12.57	12.49
φ/rad	1.57	1.58

信噪比/dB	本文算法		SET-MD方法
信噪比/dB	P₁	P₂	P₁	P₂
0	0.226	10.773	202.750	201.220
5	0.226	6.416	169.800	168.583
10	0.226	6.273	170.109	168.606
15	0.226	6.130	169.388	168.634
20	0.226	4.770	169.560	168.530

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