Wavelet de-noising Kalman filter-based Global Navigation Satellite System carrier tracking in the presence of ionospheric scintillation

Ionospheric scintillation can cause rapid changes in the phase and amplitude of Global Navigation Satellite System (GNSS) signals, resulting in degraded accuracy and robustness of signal tracking loops. Owing to the non-stationarity and non-linearity of carrier tracking under scintillation conditions, the conventional methods used to enhance the robustness of tracking loops are less effective. To overcome this problem, this study presents a wavelet de-noising adaptive Kalman filter (AKF)-based GNSS carrier tracking algorithm. Since the traditional wavelet de-noising cannot be conducted iteratively, the authors provide a sliding window-based online wavelet de-noising method to mitigate non-stationary and non-Gaussian noise caused by scintillation. After that, taking the de-noised integration as input, they employ the phase lock indicator-based AKF carrier phase estimation to avoid the nonlinearity of conventional discriminator. On this basis, the joint wavelet de-noising AKF algorithm is applied to the carrier tracking in the presence of ionospheric scintillation. Numerical results show that the proposed algorithm can improve the accuracy and robustness significantly, especially in the case of practical carrier-to-noise ratio (40 dB Hz) in moderate scintillation, the phase jitter and probability of loss-of-lock decrease about 7.5° (46%) and 73%, respectively.