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

Area of Science:

• Optical engineering
• Aerospace engineering
• Artificial intelligence

Background:

• Stable beam tracking is crucial for reliable satellite laser communications.
• Pointing, Acquisition, and Tracking (PAT) systems face challenges from external disturbances and system delays.
• Existing coarse tracking systems exhibit low dynamic response and introduce cascade delays.

Purpose of the Study:

• To propose a hybrid tracking method for improving PAT system performance.
• To address limitations in dynamic response, signal detection delays, and control lag in satellite laser communications.
• To enhance the stability and tracking accuracy of optical antennas in dynamic environments.

Main Methods:

• Implemented a hybrid tracking method utilizing long short-term memory (LSTM) neural networks for terminal pointing prediction.
• Integrated LSTM-based pointing prediction with single-detector closed-loop tracking.
• Utilized historical pointing trajectories for short-term terminal pointing predictions.

Main Results:

• The proposed LSTM-based method improves dynamic tracking capability and robust stability of the PAT system.
• The method is unaffected by orbital prediction errors and satellite attitude control errors, avoiding additional systematic errors.
• Simulations and experiments confirmed the effectiveness of the hybrid tracking approach.

Conclusions:

• The hybrid tracking method significantly enhances the performance of PAT systems in satellite laser communications.
• LSTM-based pointing prediction offers a robust alternative to ephemeris forecasts for terminal tracking.
• The integrated approach leads to more reliable and stable optical links in space.