Blind Parameter Estimation of Hybrid Networking Frequency-Hopping

被引：0
|
作者：
Fu W.-H. [1 ]
Hu Z. [1 ]
机构：
[1] School of Telecommunications Engineering, Xi'dian University, Xi'an
来源：
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2019年 / 42卷 / 04期
关键词：
Blind parameter estimation; Frequency hopping; Hybrid networking; Short-time Fourier transform; Smoothed pseudo Winger-Ville distribution;
D O I：
10.13190/j.jbupt.2018-281
中图分类号：
学科分类号：
摘要：
To solve low accuracy of parameter estimation and high complexity of algorithms in frequency hopping signal under low signal-to-noise ratio (SNR) and complex electromagnetic environment, a new algorithm combined short-time Fourier transform (STFT) with smoothed pseudo Winger-Ville distribution (SPWVD) is proposed. Firstly, the received signals are converted to time-frequency domain by using STFT, and then adaptive noise reduction is used in time-frequency domain. Secondly, the accurate frequency is estimated by adaptive clustering algorithm. Thirdly, the time-frequency information of the signals is extracted and all kinds of interference are eliminated. After the network is sorted, the rough estimation range of the hopping time can be calculated. Finally, SPWVD algorithm and a truncation threshold are used to deal with the rough estimation range, and then a precise frequency estimation is obtained. Simulations show that the parameter estimation of the algorithm has high accuracy and low complexity under the condition of hybrid networking and low SNR. The parameter estimation problem of existing frequency switching time in actual frequency hoppingcommunication system has been effectively solved. © 2019, Editorial Department of Journal of Beijing University of Posts and Telecommunications. All right reserved.
引用
收藏
页码：57 / 63
页数：6
相关论文
共 12 条
  • [1] Fu W., Wu S., Liu N., Et al., Underdetermined blind source separation of frequency hopping signal, Journal of Beijing University of Posts and Telecommunications, 38, 6, pp. 11-14, (2015)
  • [2] Sousa J.S., Vilela J.P., Uncoordinated frequency hopping for wireless secrecy against non-degraded eavesdroppers, IEEE Transactions on Information Forensics & Security, 13, 1, pp. 143-155, (2017)
  • [3] Rothman T., Random paths to frequency hopping, American Scientist, 107, 1, pp. 46-53, (2019)
  • [4] Meng L., Zhang S., Zhai X., Analysis of counter-reconnaissance and counter-jamming effectiveness for tactical radio frequency hopping communication, Fire Control & Command Control, 43, 6, pp. 76-80, (2018)
  • [5] Yu X., Guo Y., Zhang K., Et al., A network sorting algorithm based on blind source separation of multi-FH signal, Journal of Signal Processing, 33, 8, pp. 1082-1089, (2017)
  • [6] Stevens D.L., Schuckers S.A., Low probability of intercept frequency hopping signal characterization comparison using the Wigner Ville distribution and the Choi Williams distribution, Global Journal of Research In Engineering, 16, 2, pp. 2249-2596, (2016)
  • [7] Zhang C., Gui Z., Wang P., Et al., Study on optimization selection of SPWVD parameters based on Renyi entropy, China Energy and Environmental Protection, 39, 2, pp. 32-35, (2017)
  • [8] Liang Z., Lu M., A joint rapid parameter estimate method of frequency hopping signals, 2012 International Conference on Control Engineering and Communication Technology, pp. 952-954, (2012)
  • [9] Zhang K., Guo Y., Qi Z., Et al., Parameter estimation for multiple frequency-hopping signals based on sparse Bayesian reconstruction, Journal of Huazhong University of Science and Technology (Natural Science Edition), 45, 1, pp. 97-102, (2017)
  • [10] Zhao L., Wang L., Bi G., Et al., Robust frequency-hopping spectrum estimation based on sparse bayesian method, IEEE Transactions on Wireless Communications, 14, 2, pp. 781-793, (2015)
12