Micro-motion target detection algorithm of IRT based large dynamic reflection coefficient

被引：0
|
作者：
Zhou Y. [1 ]
Bi D. [1 ]
Shen A. [1 ]
机构：
[1] College of Electronic Engineering, National University of Defense Technology, Hefei
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2020年 / 42卷 / 09期
关键词：
Inverse Radon transform (IRT); Masking phenomenon; Micro-Doppler effect; Reflection coefficient; Sinusoidal frequency modulation (SFM); Time-frequency analyze;
D O I：
10.3969/j.issn.1001-506X.2020.09.08
中图分类号：
学科分类号：
摘要：
When there are micro-motion targets with large differences in the radar echo signals, the components of the weak reflection targets are often masked by the strong reflection targets and noise, which makes the weak reflection targets difficult to be detected. To solve the problem, a detection algorithm of large dynamic reflection coefficient micro-motion target is proposed. Firstly, the inverse Radon transform (IRT) algorithm is used to obtain the parameter estimation value of the strongest reflection components, and then the weak components are enhanced by removing the strong componens one by one, which makes the weak components easier to be detected. This algorithm applies to detect micro-motion targets with different reflection coefficients and has high precision of parameter estimation. The simulation experiments show that the validity of the algorithm. At the same time, the performance of the algorithm is analyzed. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：1935 / 1944
页数：9
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共 26 条
  • [1] CHEN V C, LI F, HO S S, Et al., Micro-Doppler effect in radar: phenomenon, model, and simulation study, IEEE Trans. on Aerospace and Electronic Systems, 42, 1, pp. 2-21, (2006)
  • [2] LI X, DENG B, QIN Y L, Et al., The influence of target micromotion on SAR and GMTI, IEEE Trans. on Geoscience and Remote Sensing, 49, 7, pp. 2738-2751, (2011)
  • [3] STANKOVIC L, THAYAPARAN T, DAKOVIC M, Et al., Micro-Doppler removal in radar imaging analysis, IEEE Trans. on Aerospace and Electronic Systems, 49, 2, pp. 1234-1250, (2013)
  • [4] WANG Q, PEPIN M, WRIGHT A, Et al., Reduction of vibration-induced artifacts in synthetic aperture radar imagery, IEEE Trans. on Geoscience and Remote Sensing, 52, 6, pp. 3063-3073, (2014)
  • [5] LUO Y, ZHANG Q, YUAN N, Et al., Three-dimensional precession feature extraction of space targets, IEEE Trans. on Aerospace and Electronic Systems, 50, 2, pp. 1313-1329, (2014)
  • [6] BAI X R, ZHOU F, BAO Z., High-resolution three-dimensional imaging of space targets in micromotion, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 7, pp. 3428-3440, (2015)
  • [7] PAN X Y, LIU J Q, XU L T, Et al., Extraction of micro-Doppler frequency from HRRPs of rotating targets, IEEE Access, 5, pp. 26162-26174, (2017)
  • [8] LUO Y, ZHANG Q, QIU C W, Et al., Micro-Doppler effect analysis and feature extraction in ISAR imaging with stepped-frequency chirp signals, IEEE Trans. on Geoscience and Remote Sensing, 48, 4, pp. 2087-2098, (2010)
  • [9] LI G, VARSHNEY P K., Micro-Doppler parameter estimation via parametric sparse representation and pruned orthogonal matching pursuit, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 12, pp. 4937-4948, (2014)
  • [10] SURESH P, THAYAPARAN T, OBULESU T, Et al., Extracting micro-Doppler radar signatures from rotating targets using Fourier-Bessel transform and time-frequency analysis, IEEE Trans. on Geoscience and Remote Sensing, 52, 6, pp. 3204-3210, (2014)
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