Kalman Filtering Method Based on Weighted Fusion of Frequency and Phase Discrimination for High-dynamic Carrier Tracking

Introduction: High-dynamic carrier tracking faces challenges under extreme acceleration/ jerk. Traditional methods struggle with stability. Methods: We propose a Weighted-Fusion Kalman Filter (WF-KF) method. It combines frequency and phase discriminator outputs using weighting. The Kalman filter then predicts carrier frequency and updates the Numerically Controlled Oscillator (NCO). Results: Three dynamic carrier tracking scenarios (medium-, high-, and ultra-high-dynamic) are constructed in the simulation. Compared to the Frequency-locked Loop (FLL)-assisted Phaselocked Loop (PLL) method, the proposed WF-KF method exhibits significant improvements in carrier tracking, frequency discrimination error, phase discrimination error, and bit error rate. Especially for ultra-high-dynamic situations, the FLL-assisted PLL method is in a failed state, while the proposed WF-KF method can still track stably. The simulation results have verified the effectiveness of the proposed method. Discussion: The proposed method demonstrates good tracking capability for high/ultra-high dynamic carriers. To ensure the best performance of this method, it is necessary to set the parameters related to the Kalman filter based on the observed noise and carrier dynamics. Adaptive parameter selection is a direction for future research. Conclusion: This method reliably tracks high and ultra-high-dynamic carriers with minimal tracking error and demodulation loss. It shows good potential for real-time high-dynamic signal tracking systems.