A Data Fusion Algorithm Based on Weighted Least Square for Agile Projectile's Attitude Determination

In this paper, a data fusion algorithm based on weighted least square is proposed to determine the attitude of low-rotary agile projectile. Three micro electro-mechanical system (MEMS) accelerometers are used as strapdown inertial measurement units (IMUs), and the unscented Kalman filter is used to directly estimate attitude of projectile by gravity components of measurement values of three accelerometers. The attitude estimation by three accelerometers is fused with the estimation by using three MEMS gyroscopes based on weighted least square. Experimental results on the three-axis flight test rotary table show the proposed data fusion algorithm effectively improves the precision of attitude estimation and stability of attitude determination system.