Improved generalized sidelobe cancellation algorithm in ELF communication

被引:0
|
作者
Li C. [1 ]
Jiang Y. [1 ]
Zhang N. [1 ]
Liu F. [2 ]
机构
[1] College of Electronic Engineering, Naval University of Engineering, Wuhan
[2] Academy of Mathematics and Computer Science, Yunnan Nationalities University, Kunming
来源
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | 2019年 / 46卷 / 01期
关键词
Analog circuits; Extremely-low-frequency communication; Generalized sidelobe cancellation; Linear filtering; Magnetic sensors; Noise reduction;
D O I
10.19665/j.issn1001-2400.2019.01.016
中图分类号
学科分类号
摘要
In order to improve the communication quality in extremely-low-frequency(ELF) communication, based on the generalized sidelobe cancellation(GSC) method, an improved GSC method is proposed and constructed. First, the delay summation in the main channel is replaced by the linear filtering algorithm, which is beneficial to further improving the suppression ability of incoherent noise. Second, by considering the difference in signal energy among channels, using the optimized blocking matrix can reduce the amplitude of the desired signal and improve the performance, comparing to the original blocking matrix obtained by simple subtraction among the main channels. Finally, the method using linear filtering instead of the original adaptive algorithm can achieve noise cancellation without reducing the sensitivity of the main antenna and improve the algorithm's operating speed. In order to verify the effectiveness of the proposed algorithm, an experimental platform is set up in laboratory environment and a series of control experiments are designed. Experimental results show that the designed analog circuits can suppress 50 Hz and its harmonic components and that the improved GSC algorithm is better than the original algorithm in terms of improvement of the signal-to-noise ratio(SNR) and the noise floor. © 2019, The Editorial Board of Journal of Xidian University. All right reserved.
引用
收藏
页码:98 / 105
页数:7
相关论文
共 10 条
  • [1] Ying W.W., Jiang Y.Z., Liu Y.L., Et al., A Blind Detector for Rayleigh Flat-fading Channels with Non-Gaussian Interference via the Particle Learning Algorithm, AEU-International Journal of Electronics and Communications, 67, 12, pp. 1068-1071, (2013)
  • [2] Yan B., Zhu W.H., Liu L.S., Et al., An Optimization Method for Induction Magnetometer of 0.1mHz to 1kHz, IEEE Transactions on Magnetics, 49, 10, pp. 5294-5300, (2013)
  • [3] Grosz A., Paperno E., Analytical Optimization of Low-frequency Search Coil Magnetometers, IEEE Sensors Journal, 12, 8, pp. 2719-2723, (2012)
  • [4] Coillot C., Moutoussamy J., Boda M., New Ferromagnetic Core Shapes for Induction Sensors, Journal of Sensors and Sensor Systems, 3, 1, pp. 4790-4803, (2014)
  • [5] Masmoudi A., Le-Ngoc T., Channel Estimation and Self-interference Cancellation in Full-duplex Communication Systems, IEEE Transactions on Vehicular Technology, 66, 1, pp. 321-334, (2017)
  • [6] Liu X., Xiao S., Xue X., Measurement Matrix Construction Based on Empirical Mode Decomposition, Journal of Xidian University, 45, 1, pp. 35-41, (2018)
  • [7] Chen P., Zhao Y., Liu C., Et al., Blind Beamforming Algorithm Based on Fractional Lower-order Time-frequency Decomposition, Journal of Xidian University, 44, 5, pp. 134-139, (2017)
  • [8] Jamali V., Ahmadzadeh A., Schober R., On the Design of Matched Filters for Molecule Counting Receivers, IEEE Communications Letters, 21, 8, pp. 1711-1714, (2017)
  • [9] Chen S., Wu X., Eigenvalue Proximal Support Vector Machine Algorithm Based on Eigenvalue Decoposition, Journal of Electronics & Information Technology, 38, 3, pp. 557-564, (2016)
  • [10] Gannot S., Vincent E., Markovich-Golan S., Et al., A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25, 4, pp. 692-730, (2017)