To address the problem that pulsed laser fuzes are susceptible to interference from the backscattered echoes of smoke and dust particles in battlefields,a laser echo signal separation method based on wavelet analysis has been proposed in this article. Based on Mie scattering theory and Monte Carlo method,a theoretical model of pulsed laser transmission and reception in smoke and dust environment has been established to simulate the laser echo signal with noise. The process of echo signal separation can be described as follows. Firstly,the laser echo signal noise can be removed by the threshold-based wavelet denoising method. Then peak sharpening algorithm is applied to improve the peak resolution of the echo signal and solve the problem of excessive peak overlap. Finally,continuous wavelet transform on the sharpened echo signal will be used to obtain the peak position parameters. The peak width and peak intensity information can be obtained by solving the best Gaussian fitting waveform according to the peak position value. The experimental results show that the deviation of peak position value obtained by continuous wavelet transform is within 7.9%. The peak width error and peak intensity error obtained by Gaussian function fitting are less than 2.71% and 1.82% respectively. The proposed method realizes the effective separation of the target reflection echo and the smoke backscattered echo by analyzing the pulse laser echo of the smoke and dust environment,which provides a theoretical solution for the anti-smoke interference of the pulse laser fuze in the actual battlefield environment.