The rotor current signal of maglev gyro is highly sensitive to environmental changes, therefore, noise will inevitably be introduced in the process of signal sampling. To solve this problem, an algorithm based on local mean decomposition (LMD) and fusion of Hausdorff distance and threshold denoising (TD) is proposed to reduce noise interference. Firstly, the original signal is decomposed into several PF components and a margin. Then, the noise and signal components are determined according to the Hausdorff distance between each pf component and the original signal. Then, the noise component is denoised by threshold. Finally, the noise components, signal components and margin after thresholding are superimposed to obtain the reconstructed signal, so as to realize the reconstruction of the gyroscope rotor current signal Noise reduction. The simulation results show that the signal-to-noise ratio of the reconstructed signal is 12. 86 db higher than that of the original signal, and the root mean square error is 9. 25×10 -6 A lower than that of the original signal. The de-noising results of measured signals show that the filtering gains of the de-noising algorithm for four wire sides are 40. 0%, 93. 5%, 30. 8% and 50. 0% respectively.