Integrated High-Medium-Low Orbit Satellite Positioning with Enhanced Clock Error Modeling and Adaptive Weighting Strategy

The integration of high, medium, and low Earth orbit (HML-LEO) satellites for positioning offers a promising solution to overcome the limitations of standalone global navigation satellite systems (GNSS) in challenging environments. However, existing methods often neglect higher-order satellite clock errors and fail to optimize the fusion of heterogeneous orbital data. This article proposes a novel positioning framework that integrates multi-orbit satellite signals with enhanced third-order clock drift modeling and an adaptive weighting strategy. First, a unified positioning model is established, incorporating high-accuracy satellite clock error compensation using third-order Taylor expansions. Second, an adaptive weighting algorithm is designed to balance the contributions of satellites from different orbits based on signal quality and geometric distribution. Furthermore, the Cramér-Rao Lower Bound (CRLB) for the proposed model is analytically derived, providing a theoretical benchmark for positioning accuracy. Simulations and experiments using real data from GPS (high orbit), BeiDou (medium orbit), and Iridium-Next (low orbit) satellites demonstrate that the proposed method achieves a 65% improvement in horizontal accuracy compared to conventional multi-constellation approaches. The results underscore the significance of precise clock error modeling and intelligent data fusion in advancing next-generation satellite positioning systems.