The wind speed is estimated by Kalman filter using GPS and Air Data System (ADS) measurements. For this purpose, Extended Kalman Filter (EKF) was designed, and as state variables, the wind velocity components and ADS pitot scale factor are considered. A sensor fault detection algorithm based on EKF innovation process was developed. The results were obtained for noise increment and bias conditions. Estimation errors, normalized innovations and fault detection statistics were obtained.