Due to the shape,size,distance and other factors of the target object,the feature information in the LiDAR echo signal is distributed at different scales,and the signal undergoes multipath effects,which leads to the signal phase distortion and superposition,making the idea of relying solely on wavelet thresholding to enhance the overall echo signal too simple.Moreover,the nonlinearity of the signal also affects the effectiveness of signal enhancement.In this paper,a multi scale enhancement method for LiDAR echo signals based on the CEEMDAN joint wavelet threshold algorithm is proposed.Firstly,a morphological filter is used to remove intermittent events such as pulses and intermittency from the LiDAR echo signal.Then,based on the above processing results,the CEEMDAN algorithm is used to implement effective scale decomposition of the LiDAR echo signal to effectively decompose the complex nonlinear signal into several IMF components,and to improve the accuracy of signal processing.Finally,the correlation coefficient index is used to obtain the IMF thresholds between the noise and the signals in the echo signal,and the wavelet thresholding algorithm is used to denoise the dominant IMF components,and the multi scale enhancement of the signal is realized according to the processing results.The experimental results show that the signal denoising effect is good and the enhancement performance is high when the echo signal enhancement is carried out using this method.