There are some limitations of existing methods for obtaining the key parameters of quad-rotor UAVs in the time domain. For instance, they are not adaptive to varied environment and need a large amount of computation, along with high costs and long operating time in wind tunnel test. This paper presents an identification algorithm combining UKF data pre-processing with CIFER algorithm. Firstly, the system model of the quad-rotor UAV under hovering conditions is built. Then, the measured data of the quad-rotor UAV platform is pre-processed by UKF to get rid of the noise, which is then applied to CIFER software package to identify the uncertain key parameters of the model. The result shows that the result obtained from identification of pre-processed data has a better tracking performance at the low-frequency stage, the curves fit well, and the key parameters have high credibility.