关键词: 大气数据, 传感器数据融合, 惯性导航系统, 嵌入式大气数据传感系统, 无迹卡尔曼滤波

Abstract: To solve the problems of airflow interference and inertial measurement data dispersion when the aircraft is flying at high speed，an algorithm with sensors data fusion is proposed，which estimate the real-time air data of the aircraft by Flush Air Data Sensor System(FADS）and Inertial Navigation System(INS）based on Unscented Kalman Filtering(UKF).The algorithm uses high-dimensional nonlinear system to model the relationship between inertial system and air system.Combined with the data of FADS and INS，the air speed is calculated，and then air data such as angle of attack and angle of sideslip are estimated.In the experimental results，compared with the original estimation methods such as INS direct solution and extended Kalman filter(EKF）fusion，the accuracy and system stability of estimation in this paper are improved.

Key words: Air data, Sensor data fusion, Inertial navigation system, Flush air data sensing systems, Unscented Kalman Filtering