A denoising technique is proposed based on the temporal-spatial joint analysis to improve the detection accuracy of the LiDAR bathymetry system. Utilize the strong temporal-spatial correlation between echo signals in multiple pulse trigger sampling periods of the LiDAR system， multiple set of similar echo sequences can be found through matching analysis for echo signal of any period. Convert each set of highly correlated echo sequences into a matrix for multidimensional temporal-spatial correlation analysis， and the hard-thresholding shrinkage operator is used in 2-D transform domain to attenuate the noise. Then the basic denoising results are obtained by weighted aggregation. The matching analysis is performed again on the basic denoising data set， and the multidimensional analysis based on the Wiener shrinkage operator is further applied to remove the residual noise. The real signals can be separated from uncorrelated noise. Experimental results demonstrate that the proposed method achieves good effect in noise suppression and edge preservation compared with the widely used LiDAR denoising methods， and improves the peak signal to noise ratio of seafloor signal.