Information fusion and reconstruction of key sensors in a flight control system in constant wind field based on two stage EKF

Abstract

Kalman filter is of importance in information fusion and reconstruction of key sensors in a flight control system. Two stage kalman filter is able to solve the filtering problem which caused by an unknown constant bias in a filtering model. Extended kalman filter is one simple but effective method to deal with nonlinear system filtering problem. In this paper, constant wind field is regarded as the unknown constant bias in trajectory velocity measurement innovatively. Employing two stage extended kalman filter (TSEKF) realizes information fusion of key sensors in a flight control system. When air velocity, angle of attack and angle of sideslip sensors are working, TSEKF realizes estimations of air velocity, angle of attack, angle of sideslip and wind velocity. When they are out of work, TSEKF realizes information reconstruction of air velocity, angle of attack, angle of sideslip.