VHF communication is widely used in civil aviation, but it is highly susceptible to various noise interferences. The traditional method has poor denoising effect and does not eliminate inherent interference, this paper proposes an adaptive Kalman filter algorithm based on wavelet analysis. In this algorithm, a new threshold function is proposed in the wavelet analysis, and in the adaptive Kalman filter algorithm, an adaptive factor is added to adjust the window length to adjust the filter gain, which can effectively avoid the filter divergence. This paper randomly selects VHF speech signals of four different frequencies in a certain period of time and filtered by the proposed algorithm. The signal-to-noise ratio, root mean square error, signal waveform and spectrogram are analyzed. The results show that the algorithm can effectively remove the noise in VHF speech signal, obtain higher signal-to-noise ratio and smaller root mean square error, and further improve the quality of speech.