Human micro-Doppler frequency estimation method based on continuous wave radar

被引：0
|
作者：
Ding Y. [1 ]
Liu R. [1 ]
Xu X. [1 ]
机构：
[1] School of Physics and Electronics, Central South University, Changsha
来源：
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2022年 / 53卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Continuous wave radar; Exponential smoothing prediction; Micro-Doppler frequency; Time-frequency analysis; Viterbi algorithm;
D O I：
10.11817/j.issn.1672-7207.2022.04.012
中图分类号：
学科分类号：
摘要：
Aiming at the problem that the target signal is hard to identify in frequency ambiguity region of continuous wave radar(CWR), and the path bifurcation problem of traditional Viterbi algorithm in instantaneous frequency estimation, a novel theoretical method to estimate the micro-Doppler frequencies of human specific scattering parts from CWR echo was proposed with a united application of a modified Viterbi algorithm and the exponential smoothing prediction technology. The smoothing coefficient of the exponential smoothing method was adjusted dynamically according to the local characteristics of radar echo, and a new penalty function based on cubic exponential smoothing prediction was defined. The results show that the proposed method effectively suppresses the path bifurcation problem in frequency ambiguity region. Compared with the peak detection algorithm based on short-time Fourier transform and traditional Viterbi algorithm, the root mean square error of left arm micro-Doppler frequency estimation obtained from the proposed method decreases significantly. The employed dynamic search method makes improvement of the traditional whole-plane search and increases the efficiency of searching the optimal paths considerably. ©2022, Central South University Press. All right reserved.
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页码：1273 / 1280
页数：7
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共 20 条
  • [11] TANG Jingtian, CAI Jianhua, REN Zhengyong, Et al., Hilbert-Huang transform and time-frequency analysis of magnetotelluric signal, Journal of Central South University(Science and Technology), 40, 5, pp. 1399-1405, (2009)
  • [12] WU Wei, WANG Guohong, SUN Jinping, Polynomial radon-polynomial Fourier transform for near space hypersonic maneuvering target detection, IEEE Transactions on Aerospace and Electronic Systems, 54, 3, pp. 1306-1322, (2018)
  • [13] TANG Jingtian, LI Guang, ZHOU Cong, Et al., Power-line interference suppression of MT data based on frequency domain sparse decomposition, Journal of Central South University, 25, 9, pp. 2150-2163, (2018)
  • [14] DJUROVIC I, STANKOVIC L., An algorithm for the Wigner distribution based instantaneous frequency estimation in a high noise environment, Signal Processing, 84, 3, pp. 631-643, (2004)
  • [15] LI Po, ZHANG Qinghai, An improved Viterbi algorithm for IF extraction of multicomponent signals, Signal, Image and Video Processing, 12, 1, pp. 171-179, (2018)
  • [16] SU Xiaofan, XIAO Rui, ZHU Mingzhe, Method for IF estimation of multicomponent FM signals, Journal of Xidian University(Science and Technology), 46, 1, pp. 51-56, (2019)
  • [17] DING Yipeng, LIN Xiaoyi, HUANG Guowei, Et al., Hough-based target tracking algorithm for continuous wave through wall radar, 2019 International Conference on Microwave and Millimeter Wave Technology(ICMMT), pp. 1-3, (2019)
  • [18] CHEN Shiqian, DONG Xingjian, XING Guanpei, Et al., Separation of overlapped non-stationary signals by ridge path regrouping and intrinsic chirp component decomposition, IEEE Sensors Journal, 17, 18, pp. 5994-6005, (2017)
  • [19] BOULIC R, THALMANN N M, THALMANN D., A global human walking model with real-time kinematic personification, The Visual Computer, 6, 6, pp. 344-358, (1990)
  • [20] SUN Yunwu, Statistics-data collection, collation and analysis, pp. 321-325, (2007)
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