Navigation Algorithms for Precision Re-Entry of a Launcher First-Stage

This paper outlines the design and preliminary validation of navigation algorithms for reusable launchers, employing an Error-State Kalman Filtering approach. The algorithm integrates data from GNSS, IMU, radar altimeters and virtual air data estimation to achieve high precision across all mission phases, including hypersonic re-entry and precision landing. Sensor fusion ensures robustness against GNSS outages and environmental disturbances, by means of sensor models and INS strapdown integration. Monte Carlo simulation’s results demonstrate compliance with performance criteria, validating the algorithm’s effectiveness for real-time guidance and control in reusable space transportation systems.