Open AccessParameter estimation of frequency hopping signal based on MWC–MSBL reconstruction
Author(s) -
Yixuan Guo,
Zhi Li,
Jian Li,
Jianhua Zhou
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0987
Subject(s) - frequency hopping spread spectrum , computer science , frequency domain , signal (programming language) , estimation theory , frequency modulation , wideband , algorithm , signal reconstruction , time domain , control theory (sociology) , signal processing , telecommunications , artificial intelligence , electronic engineering , bandwidth (computing) , radar , computer vision , programming language , control (management) , engineering
Aiming at the problem that single‐network hopping signals have not fully utilised its frequency domain sparse characteristic in the parameter estimation, this study proposes a parameter estimation of frequency hopping (FH) signal based on multi‐measurement vector sparse Bayesian learning (MSBL) in modulation wideband converter (MWC). Since the FH signal is sparse in the frequency domain, the authors apply the MSBL method to estimate its parameters. After the signal is sampled by the MWC, the MSBL algorithm is used to reconstruct its support set. Then the time–frequency ridge method is used to estimate the signal's hop duration, time‐hopping, and carrier frequency based on the time–frequency map. Simulation experiments show that under the condition of low signal‐to‐noise ratio, the parameter estimation performance in the case can be improved by up to 65% and anti‐noise performance can be improved up to 6 db compared with the existing method. The result is very close to the Nyquist full sampling and can greatly improve the accuracy of the FH signal parameter estimation in the MWC system and relieve the pressure of the hardware.