Parallelized and adaptive square-root unscented Kalman filter for carrier recovery in satellite-to-ground coherent optical communications

Abstract

An adaptive square-root unscented Kalman filter with a parallelized architecture for carrier recovery is proposed in QPSK based satellite-to-ground coherent optical communication systems. A new observation model is raised in the proposed scheme to make the state estimation more accurate. The process noise covariance (Q) and the measurement noise covariance (R) are adaptively estimated to make them consistent with their theoretical covariance. For verification of the feasibility of the proposed scheme, corresponding simulations of carrier recovery in satellite-to-ground laser links are carried out and compared with the scheme that is based on linear Kalman filter (LKF). The simulation results demonstrate that, compared with parallelized LKF, the proposed scheme has a wider range of block size and laser linewidth options, and it can relax the required transmit power by up to 0.5-3 dB under different zenith angle at the same BER. Moreover, the proposed scheme can achieve high estimation accuracy and fast tracking capability simultaneously in the case of dynamic frequency offset with better tolerance against the initial errors in Q and R.