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A flight data processing method is proposed for the measurement error of attitude angular rate in frequency domain identification of small unmanned helicopter model. The method adopts the flight test frequency sweep test technology to ensure that the excitation signal can meet the requirements of flight data for model identification in different frequency bands. The Kalman filter based on colored noise was designed to reduce the impact of turbulent wind field on flight measurement data, and a method of data preprocessing was used for the flight measurement data to eliminate measurement noise, outliers, DC components and low frequency components. The verification was performed in each channel of the small unmanned helicopter system, the verification results show that the proposed flight data processing method can meet the requirements of attitude angular rate data accuracy for the identification of small unmanned helicopter model and provide high quality flight data for accurate modeling.