The carrier synchronization algorithm of the autonomous radio for deep space is studied.When the signal modulation is unknown,this paper improves the existing universal carrier synchronization loop for multiple modula...The carrier synchronization algorithm of the autonomous radio for deep space is studied.When the signal modulation is unknown,this paper improves the existing universal carrier synchronization loop for multiple modulations,expands the frequency tracking range of the loop,proposes a Tong detection-based M-ary Phase Shift Keying(M-PSK)signal locking detection algorithm to rapidly and effectively determine whether the current phase discrimination mode matches the modulation mode,so as to independently choose whether to switch the phase discrimination mode.Through theoretical analysis and comparison,it is described that the total detection probability of the algorithm proposed in this paper is significantly higher than the probability of single lock detection.Simulation results show that the algorithm has high detection probabiUty and low computational complexity at a low signal to noise ratio.展开更多
Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is aut...Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is automatic when the signal to noise ratio（SNR） is unknown.If the frequency-locked loop（FLL） or the phase-locked loop（PLL） with fixed loop bandwidth, or Kalman filter with fixed noise variance is adopted, the accretion of estimation error and filter divergence may be caused.Therefore, the Kalman filter algorithm with adaptive capability is adopted to suppress filter divergence.Through analyzing the inadequacies of Sage–Husa adaptive filtering algorithm, this paper introduces a weighted adaptive filtering algorithm for autonomous radio.The introduced algorithm may resolve the defect of Sage–Husa adaptive filtering algorithm that the noise covariance matrix is negative definite in filtering process.In addition, the upper diagonal（UD） factorization and innovation adaptive control are used to reduce model estimation errors,suppress filter divergence and improve filtering accuracy.The simulation results indicate that compared with the Sage–Husa adaptive filtering algorithm, this algorithm has better capability to adapt to the loop, convergence performance and tracking accuracy, which contributes to the effective and accurate carrier tracking in low SNR environment, showing a better application prospect.展开更多
基金Supported by Program for New Century Excellent Talents in University(NCET-12-0030)National Natural Science Foundation of China(91438116)
文摘The carrier synchronization algorithm of the autonomous radio for deep space is studied.When the signal modulation is unknown,this paper improves the existing universal carrier synchronization loop for multiple modulations,expands the frequency tracking range of the loop,proposes a Tong detection-based M-ary Phase Shift Keying(M-PSK)signal locking detection algorithm to rapidly and effectively determine whether the current phase discrimination mode matches the modulation mode,so as to independently choose whether to switch the phase discrimination mode.Through theoretical analysis and comparison,it is described that the total detection probability of the algorithm proposed in this paper is significantly higher than the probability of single lock detection.Simulation results show that the algorithm has high detection probabiUty and low computational complexity at a low signal to noise ratio.
基金supported by Program for New Century Excellent Talents in University of China (No.NCET-120030)National Natural Science Foundation of China (No.91438116)
文摘Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is automatic when the signal to noise ratio（SNR） is unknown.If the frequency-locked loop（FLL） or the phase-locked loop（PLL） with fixed loop bandwidth, or Kalman filter with fixed noise variance is adopted, the accretion of estimation error and filter divergence may be caused.Therefore, the Kalman filter algorithm with adaptive capability is adopted to suppress filter divergence.Through analyzing the inadequacies of Sage–Husa adaptive filtering algorithm, this paper introduces a weighted adaptive filtering algorithm for autonomous radio.The introduced algorithm may resolve the defect of Sage–Husa adaptive filtering algorithm that the noise covariance matrix is negative definite in filtering process.In addition, the upper diagonal（UD） factorization and innovation adaptive control are used to reduce model estimation errors,suppress filter divergence and improve filtering accuracy.The simulation results indicate that compared with the Sage–Husa adaptive filtering algorithm, this algorithm has better capability to adapt to the loop, convergence performance and tracking accuracy, which contributes to the effective and accurate carrier tracking in low SNR environment, showing a better application prospect.
