Satellite Integrated Navigation Algorithm Based on AREKF

With the increasing frequency of space exploration activities, the importance of satellite autonomous navigation continues to grow. To address the issue of the degraded integrated navigation accuracy caused by measurement anomalies in spaceborne GNSS receivers, this paper proposes an improved algorithm based on Adaptive Robust Extended Kalman Filter (AREKF). The algorithm uses the innovation sequence of Kalman filtering as a test statistic and constructs an adaptive adjustment factor based on the theoretical standard deviation of observations. This enables dynamic adjustment of the observation noise covariance matrix, effectively isolating abnormal measurements and ensuring the accuracy and stability of integrated navigation. Simulation results validate the effectiveness of the proposed method.