LIU Gaohui, LIU Jun. Research on the carrier tracking method of single-carrier communication signal based on extended particle filter algorithm[J]. Microelectronics & Computer, 2021, 38(12): 61-68. DOI: 10.19304/J.ISSN1000-7180.2021.1147
Citation: LIU Gaohui, LIU Jun. Research on the carrier tracking method of single-carrier communication signal based on extended particle filter algorithm[J]. Microelectronics & Computer, 2021, 38(12): 61-68. DOI: 10.19304/J.ISSN1000-7180.2021.1147

Research on the carrier tracking method of single-carrier communication signal based on extended particle filter algorithm

  • Aiming at solving low carrier tracking accuracy and slow response speed in high-speed mobile communication scenarios, a carrier tracking method based on Extended Particle Filter (EPF) is proposed in this paper. This method combines extended Kalman filter and particle filter to realize the function of loop filter in Costas loop. The output value of inverse tangent discriminator is taken as the observation, and the phase difference, carrier frequency offset and frequency offset change rate between local carrier and received signal are taken as the state variables of extended Kalman filter. Firstly, this paper gives the high dynamic signal model in the scene of high-speed mobile communication. Secondly, the carrier tracking method based on extended particle filter is theoretically analyzed. Thirdly, the working steps of the carrier tracking method are given. Finally, the combination algorithm of frequency locked loop and phase locked loop, extended Kalman filter The carrier tracking process of single carrier communication signal based on particle filter and extended particle filter is simulated. The results show that the tracking loop based on extended particle filter is more suitable for high dynamic scenarios. Compared with the tracking loop based on extended Kalman filter and particle filter, the frequency error range is reduced to 50% and 67% respectively, and the phase error range is reduced to 57% compared with the tracking loop based on extended Kalman filter.
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