Abstract: The strap-down inertial navigation system (SINS) is a commonly-used sensor for autonomous underground navigation that can be used for shearer positioning at a coal mine working face. The determination of the initial attitude angle of the shearer is the premise of navigation and positioning,and the performance of the subsequent navigation depends largely on the accuracy of the initial attitude matrix. The severe vibration induced by the cutting coal wall of shearer will make the SINS more sensitive to high frequency noise,which will degrade the performance of the initial alignment for the shearer. In order to overcome the low precision and slow convergence rate of the existing initial alignment algorithm with strong vibration conditions in underground coal mines,a novel initial alignment method based on frequency domain isolation is introduced. Firstly,according to the structural characteristics of shearer, the dynamic model of shearer when cutting the coal wall is constructed based on the mass block method. In this respect,the motion state of the shearer fuselage when cutting coal wall is analyzed and investigated by using the Ode45 function based on Runge-Kutta variable step size algorithm provided by MATLAB. Then,Fourier transform is used to transform the time domain information into frequency domain,and the frequency range of the fuselage when the shearer cutting the coal wall can be determined. On the basis of the traditional initial alignment algorithm,the concept of frequency domain isolation operator is incorporated and Finite Impulse Response (FIR) filter is designed to suppress the high frequency noise. The experiment results show that the proposed method can effectively suppress the high frequency vibration,and improve the convergence rate and accuracy of the initial alignment. The steady state error of pitch angle and roll angle is less than 0. 1°,and the steady state error of heading angle is less than 0. 7°,which meets the requirements of subsequent fine alignment.