Fast alignment using rotation vector and adaptive Kalman filter

A fast and convenient alignment method is proposed. To improve the speed of convergence, we used rotation vectors instead of traditional Euler angles. Furthermore, we developed an algorithm to automatically tune the measurement noise covariance matrix using adaptive Kalman filtering. Finally, the developed algorithms were applied to an aerial imaging system to automatically geo-locate the centers of the images.