In the inertial navigation system, in order to improve the attitude measurement accuracy of the gyroscope and suppress the influence of lowfrequency noise, the wavelet transform method is used to fuse the gyroscope and accelerometer data to solve the attitude angle. In this paper, the data collected by the gyroscope is firstly decomposed into two layers of wavelets to remove lowfrequency components and unstable signals, and reconstructed with highfrequency components to obtain filtered gyroscope data. Then use the data collected by the accelerometer to calculate the attitude angle, which is used to continuously iterate the initial quaternion, find the gravity vector from the initial quaternion, and then find the error from the cross product of the gravity vector, and perform PID control to correct the gyroscope’s angle. Finally, the corrected and filtered gyro data are used to calculate the new quaternion using the RungeKutta method, and the quaternion is used to adjust the negative gain, and finally the accurate attitude angle is calculated. The simulation results show that the accuracy of calculating the attitude angle is increased by 80%,which can effectively suppress lowfrequency noise and calculate the attitude angle more accurately, thereby further improving the positioning accuracy of the navigation system.