University of Electronic Science and Technology of China
Kalman filtering (KF) has good potential in fast rotation of state of polarization (RSOP) tracking. Different measurement equations cause the diverse RSOP tracking performances. We compare the conventional KF (CKF) and the modified KF (MKF)that have different measurement equations. Semi-theoretical analysis indicates the lower conditional variances of measurement residual and process noise of MKF. Compared with CKF, the MKF has > 3-dB optical signal-to-noise ratio (OSNR) improvement at the 10-MHz scrambling rate in simulation. For MKF, more significant tracking speed improvement exists in lower OSNR. MKF can be smoothly combined with adaptive algorithm, which outperforms adaptive CKF throughout the simulations.