Blind Symbol Rate Estimation for FSK Signals Based on Time-Frequency Enhancement and Periodic Feature Reinforcement

Aiming at the problem of large errors in blind symbol rate estimation of Frequency Shift Keying (FSK) signals under low signal-to-noise ratio (SNR) and multipath fading, this paper proposes a blind estimation method based on time-frequency enhancement and periodic feature reinforcement. The method adaptively adjusts the time-frequency energy values to compensate for the energy discontinuities between consecutive identical symbols. The peak-to-average ratio (PAR) differential curve of the time-frequency diagram is further autocorrelated and analyzed in the frequency domain to reinforce the symbol period features while suppressing noise interference. Finally, the symbol rate estimation is completed through spectral peak detection. The simulation results show that the proposed algorithm achieves high estimation accuracy under low SNR conditions and remains robust in multipath fading channels.