Design of robust positioning algorithm for low-earth orbit satellites: inter-satellite link interruption compensation based on adaptive UKF and backtracking smoothing

Low-Earth Orbit (LEO) satellite constellations have emerged as a promising solution for global navigation and positioning, particularly in Global Navigation Satellite System (GNSS)-denied environments. However, the rapid motion of LEO satellites and frequent inter-satellite link (ISL) interruptions pose significant challenges to maintaining continuous and reliable positioning. This paper proposes a robust positioning algorithm that integrates an Adaptive Unscented Kalman Filter (AUKF) with backtracking smoothing to address ISL interruptions. The algorithm dynamically adjusts the filter parameters based on real-time link quality and employs a backward smoothing mechanism to recover lost information during outages. A comprehensive mathematical framework is developed to model the satellite dynamics, measurement uncertainties, and adaptive mechanisms. Simulations under varying ISL interruption durations and noise levels demonstrate that the proposed algorithm achieves a 40% improvement in positioning accuracy compared to conventional UKF methods, with a root mean square error (RMSE) reduction from 12.3 m to 7.4 m in severe interruption scenarios. The results highlight the algorithm’s robustness in compensating for discontinuous measurements, making it a viable solution for LEO-based navigation systems.