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Many domestic and foreign research institutions are committed to the four-rotor UAV flight control attitude and high hover stability research, in order to achieve the four-rotor UAV"s autonomous flight. The four-rotor unmanned aerial vehicle (UAV) is a multi-input, strong coupling, multivariable, underactuated system. Its stability, data transmission reliability, accuracy and real-time performance play a decisive role in aircraft performance. According to the existing UAV platform, the latest research frontier literature, ARM embedded system as the host computer, designed a UAV data acquisition for the four-axis UAV hover movement test link instability in the existing Extended Kalman filter (EKF), combined with quadratic optimal control to predict the barometer optimal initial matrix value for open source programming. From the expansion of the Kalman filter to establish and optimize the original program barometer program rigorous discussion, convergence and write flight control, and ultimately in the software anonymous Kechuang ground station, through the UAV on the barometer large number of real-time hovering data acquisition The experimental results show that the proposed method of UAV data acquisition and expansion Kalman filtering is effective and has good application and popularization value.