Interacting multiple model cubature Kalman filter for geomagnetic/ infrared projectile attitude measurement

When GPS signals are interrupted artificially or by environmental interferences, it is impossible to determine the attitude of a spinning projectile using the conventional method. The geomagnetic field and atmospheric infrared radiation field are inherent physical properties of the Earth; in this study, corresponding geomagnetic and infrared attitude measurement models are established to improve reliability. Anticipating sensor output failure in the flight process, the interacting multiple model cubature Kalman filter (IMMCKF) algorithm is designed to improve the adaptability of the system. The effectiveness of the algorithm is verified by semi-physical experiments, which showed that the IMMCKF algorithm, with high accuracy and strong anti-interference, is significantly better than the cubature Kalman filter (CKF) and the interacting multiple model extended Kalman filter When GPS signals are interrupted artificially or by environmental interferences, it is impossible to determine the attitude of a spinning projectile using the conventional method. The geomagnetic field and atmospheric infrared radiation field are inherent physical properties of the Earth; in this study, corresponding geomagnetic and infrared attitude measurement models are established to improve reliability. Anticipating sensor output failure in the flight process, the interacting multiple model cubature Kalman filter (IMMCKF) algorithm is designed to improve the adaptability of the system. The effectiveness of the algorithm is verified by semi-physical experiments, which showed that the IMMCKF algorithm, with high accuracy and strong anti-interference, is significantly better than the cubature Kalman filter (CKF) and the interacting multiple model extended Kalman filter (IMMEKF).