Composite axis beam tracking control with LSTM-based pointing trajectory prediction for satellite laser...

In satellite laser communications, maintaining stable beam tracking is a prerequisite for establishing reliable optical links. To overcome relative motion between terminals, platform vibration, and other external disturbances, the pointing, acquisition, and tracking (PAT) system typically employs a composite axis control structure, which utilizes sensors to detect deviations between incident light and the optical axis, then corrects the pointing of the optical antenna through the drive unit. To address issues such as the low dynamic response characteristics of coarse tracking systems, receiving optical signal detection delays, closed-loop control lag, and coarse-fine tracking cascade delays, this paper proposes a hybrid tracking method based on long short-term memory (LSTM) neural networks for terminal pointing prediction. During the tracking phase, LSTM uses historical pointing trajectories to accomplish short-term pointing predictions for the terminal. Compared to using ephemeris forecasts, this method is not affected by factors such as orbital prediction errors and satellite attitude control errors, and does not introduce additional systematic errors. The integration of the pointing prediction mechanism and single-detector closed-loop tracking improves the dynamic tracking capability and robust stability of the PAT system. Simulation and experiments verified the effectiveness of the proposed method.