An Adaptive Robust Filter for GNSS/INS Integrated Navigation System

The integration of the Global Navigation Satellite System (GNSS) and the Inertial Navigation System (INS) capitalizes on their complementary attributes to provide dependable position data. This study introduces an innovative technique that utilizes an interactive multiple model-based adaptive robust enhanced Kalman filter (IMM-AREKF) algorithm. The algorithm is designed to tackle challenges like skewed GNSS observations due to a biased system model or substantial instantaneous measurement discrepancies. It enhances the accuracy of GNSS/INS navigation systems by dealing with issues such as system model ambiguity, errors in noise statistics, short-lived interference during the measurement phase, among others. The efficacy of the algorithm is confirmed through a simulation experiment, the outcome of which attests to its utility.