The present invention provides an angular accelerometer signal adaptive denoising method based on wavelet analysis. Compared with a conventional wavelet analysis denoising method, the method of the present invention comprises the steps of calculating the difference quotient of the wavelet energy entropies and the energy entropies of a signal with noise and a noisy signal to determine an optimal wavelet decomposition level of the signal with noise, applying the median filtering to evaluate a noise width and a noise standard deviation, and combining a 3 sigma criterion to set a threshold value to thereby carry out the adaptive filtering. At the aspect of the threshold value selection, the method has better effects by being compared with a conventional heuristic sure criterion, a maximum and minimum value criterion and a penalty criterion. The above methods have better effects on the denoising processing of a periodic signal and a high-dynamic signal of a molecule type liquid-ring angular accelerometer.