An EL SHAKF based integration scheme for Gyro Thermal Magnetic Coupling Heading Effect Drift Compensation in INS

Inertial navigation system (INS) is widely equipped in various vehicles for overcoming GPS-challenging environments. The thermal-magnetic coupling heading-effect drift (thermal-magnetic drift) of INS is a multi-physics coupling error related to carrier maneuver, which cannot be compensated well by traditional methods. In this paper, the source of gyro thermal-magnetic drift are analyzed and an Ensemble Learning (EL) and Sage-Husa adaptive Kalman filter (SHAKF) based integration scheme for the thermal-magnetic drift compensation in high-grade INS is established. In the integrated system, the geomagnetic field strength calculated by International Geomagnetic Reference Field (IGRF) model and temperature information measured by sensors are selected as input of the thermal-magnetic drift prediction model. The gyro biases estimated by exponential fading SHAKF are taken as target in training phase. The EL algorithms, LSBoost and Bagging, are used for training when GPS data is available. The gyro thermal-magnetic drift is predicted and compensated by the trained model during GPS outages. Land and sea tests show its effectiveness on compensate the gyro thermal-magnetic drift of the proposed method.