Multicomponent LFM signal detection and parameter estimation method based on FRFT

被引：0
|
作者：
Song Y. [1 ]
Huang Y. [1 ]
Zhang H. [1 ]
Qin Z. [1 ]
Gao W. [1 ]
机构：
[1] Information and Navigation College, Air Force Engineering University, Xi'an
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2020年 / 46卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Aimed searching; Fractional Fourier Transform (FRFT); Linear Frequency Modulation (LFM) signal; Parameter estimation; S-G filtering;
D O I：
10.13700/j.bh.1001-5965.2019.0430
中图分类号：
学科分类号：
摘要：
Aimed at the low searching efficiency of traditional methods, this paper, using aimed searching strategy, proposes a fast and accurate algorithm for detecting and estimating multicomponent Linear Frequency Modulation (LFM) signal parameters.The approximate relation between the power spectrum width and rotation angle of LFM signal in fractional domain is deduced.This paper presents an efficient algorithm for searching the optimal rotation angle using the variation law of power spectrum amplitude with rotation angle in fractional domain.And it is concluded that the computation of this algorithm is small and has great advantages compared with the traditional algorithm.In the case of low SNR, two times of S-G filtering can significantly improve the detection probability. Simulation results show that the algorithm can reliably detect and accurately estimate multicomponent LFM signal parameters under the condition of low SNR and interference between components. © 2020, Editorial Board of JBUAA. All right reserved.
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页码：1221 / 1228
页数：7
相关论文
共 15 条
  • [1] RAO P, TAYLOR F J., Estimation of instantaneous frequency using the discrete wigner distribution, Electronics Letters, 26, 4, pp. 246-248, (1990)
  • [2] CHOI H, WILLIAMS W J., Improved time-frequency representation of multicomponent signals using exponential kernels, IEEE Transactions on Signal Processing, 37, 6, pp. 862-871, (1988)
  • [3] LI J Q, JIN R H, GENG J P, Et al., Detection and estimation of multi-component LFM signals based on Gauss short-time fractional Fourier transform, Journal of Electronics & Information Technology, 29, 3, pp. 570-573, (2007)
  • [4] TAO R, LI Y L, WANG Y., Short-time fractional Fourier transformand its applications, IEEE Transactions on Signal Processing, 58, 5, pp. 2568-2580, (2010)
  • [5] YIN Q B, SHEN L R, LU M Y, Et al., Selection of optimal win-dow length using STFT for quantitative SNR analysis of LFMsignal, Journal of Systems Engineering and Electronics, 24, 1, pp. 26-35, (2013)
  • [6] QI L, TAO R, ZHOU S Y, Et al., Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform, Science in China(Series E), 33, 8, pp. 749-759, (2003)
  • [7] WANG P, YANG J Y, DU Y M, Et al., Fractional order autocorrelation and FrFT LFM signal parameter estimation, Journal of University of Electronic Science and Technology of China, 35, 2, pp. 179-182, (2006)
  • [8] AKAY O, BOUDREAUX-BARTELS G F., Fractional convolution and correlation via operator methods and an application to detection of linear FM signals, IEEE Transactions on Signal Processing, 49, 5, pp. 979-993, (2001)
  • [9] QIU Z Y, CHEN R, WANG Y M, Et al., Fast detection method of linear frequency modulation signal under sampling based on FRFT, Chinese Journal of Electronics, 40, 11, pp. 2165-2170, (2012)
  • [10] LIU S, SHAN T, TAO R, Et al., Sparse discrete fractional Fourier transform and its applications, IEEE Transactions on Signal Processing, 62, 24, pp. 6582-6595, (2014)
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