One navigation scheme by integrating inertial navigation system (INS)/optical flow/magnetometer/barometer is proposed based on the extended Kalman filtering. Through data fusion of INS, optical flow and barometer, the speed and position of unmanned aerial vehicle (UAV) are estimated. When UAV is at rest or in motion with constant velocity, the UAV attitude is estimated by means of data fusion of gyro, accelerometer, magnetometer, and optical flow. When UAV is accelerated or decelerated, the gyroscope data is used to estimate the UAV attitude. The experimental results show that, the speed error for UAV is reduced from the maximum 20 m/s to 10 m/s, and the angle error is reduced from the maximum 80° to 10°. This scheme can effectively solve the cumulative error problem of velocity, position and attitude estimation.