Tightly Coupled LEO SOP/INS Integrated Navigation Using an Adaptive Unscented Kalman Filter Framework

With the rapid development of low earth orbit (LEO) constellations, LEO signals of opportunity (LEO-SOP) navigation has attracted extensive attention for positioning services in complex-denied environments. However, LEO-SOP suffers from limited coverage multiplicity and time-varying observation noise, leading to degraded positioning accuracy and availability. To address this issue, this paper applies an innovation-based adaptive unscented Kalman filtering (AUKF) scheme to LEO/inertial navigation system (INS) tightly coupled integration. By constructing the innovation sequence, the impact mechanism of noise uncertainty on filtering performance is analyzed, and an online noise covariance estimation strategy is designed to achieve dynamic adaptive compensation for both process and measurement noise. Simulation results demonstrate that the proposed method effectively suppresses the destabilizing effects of LEO observation noise and significantly improves the robustness and estimation accuracy of the filter in complex environments.