This paper describes singular value decomposition (SVD) aided extended Kalman filter (EKF) for nanosatellite's attitude estimation. The development of the filter kinematic/dynamic model, and the measurement models of the sun sensors, and the magnetometers which are used to generate vector measurements is presented. Vector measurements are used in SVD for satellite attitude determination purpose. In the proposed method EKF inputs are coming from SVD as the linear measurements of attitude angles and their error covariance. In this step, UD is factorizing the attitude angles error covariance with forming the measurements in order to obtain the appropriate inputs for the EKF. Results are presented and analyzed in addition that the necessity of the sub-step which is the UD factorization on the measurement covariance is discussed. On the whole, the filter meets the expected accuracy, and robustness.