scholarly journals A Method for the Micro-Motion Signal Separation and Micro-Doppler Extraction for the Space Precession Target

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 130392-130404 ◽  
Author(s):  
Xuguang Xu ◽  
Cunqian Feng ◽  
Sisan He
Keyword(s):  
Signal Separation ◽  
Motion Signal ◽  
Micro Motion

scholarly journals Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1637
Author(s):  
Saiqiang Xia ◽  
Jun Yang ◽  
Wanyong Cai ◽  
Chaowei Zhang ◽  
Liangfa Hua ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Singular Value ◽  
Fluctuation Analysis ◽  
Variational Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
The Real ◽  
Motion Signal ◽  
Mode Decomposition ◽  
Radar Echo ◽  
Micro Motion

In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper. The CVMD is extended from variational mode decomposition (VMD), which is a recently introduced technique for adaptive signal decomposition, limited to only dealing with the real signal. Thus, the VMD is extended from the real domain to the complex domain firstly. Then, the optimal effective order of singular value is obtained by singular value decomposition (SVD) to solve the problem of under-decomposition or over-decomposition caused by unreasonable choice of decomposition layer, it is more accurate than detrended fluctuation analysis (DFA) and empirical mode decomposition (EMD). Finally, the strongly correlated modes and weakly correlated modes are judged by calculating the Mahalanobis distance between the band-limited intrinsic mode functions (BLIMFs) and the original signal, which is more robust than the correlation judgment methods such as computing cross-correlation, Euclidean distance, Bhattachryya distance and Hausdorff distance. After the weak correlation modes are eliminated, the signal is reconstructed locally, and the separation of the micro-motion signal is realized. The experimental results show that the proposed method can filter out the strong clutter component and the fuselage component from radar echo more effectively than the local mean decomposition (LMD), empirical mode decomposition and moving target indicator (MTI) filter.

scholarly journals Separation and feature extraction of micro‐motion signal of ballistic target

2021 ◽  
Author(s):  
Yuxi Li ◽  
Cunqian Feng ◽  
Xuguang Xu ◽  
Lixun Han ◽  
Dayan Wang
Keyword(s):  
Feature Extraction ◽  
Motion Signal ◽  
Micro Motion

A Modified JadeR for Signal Separation under Gaussian Noise

2018 ◽  
Vol 5 (3) ◽  
pp. 27-31
Author(s):  
Muna Fatnan ◽  
◽  
Zahir Hussain ◽  
Hind Mohammed ◽  
◽  
...  
Keyword(s):  
Gaussian Noise ◽  
Signal Separation

Micro-motion Targets Resolution in a High Noise Environment

2010 ◽  
Vol 32 (11) ◽  
pp. 2630-2635
Author(s):  
Yong-sheng Guan ◽  
Qun-sheng Zuo ◽  
Hong-wei Liu
Keyword(s):  
High Noise ◽  
Noise Environment ◽  
Micro Motion

Underdetermined Blind Radar Signal Separation Based on ICA

2010 ◽  
Vol 32 (4) ◽  
pp. 919-924 ◽  
Author(s):  
Xiao-jun Chen ◽  
Hao Cheng ◽  
Bin Tang
Keyword(s):  
Signal Separation ◽  
Radar Signal
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