In order to improve the denoising effect of LIDAR point cloud,a double scale algorithm is proposed.Firstly,the LIDAR point cloud is initially denoised by tensor voting matrix.Secondly,dynamic radius filtering is applied to denoise large scale noise,effectively improving the filtering accuracy and algorithm efficiency.Then,the improved bilateral filtering algorithm is used to denoise the small scale point cloud noise,and the weight coefficient smooth the point cloud,while being able to obtain the detail features of the point cloud.Finally,the algorithm flow is given.The experiments show that double scale algorithm can remove noise at different scales,and the denoised point cloud model can retain the geometric characteristics in details,and the evaluation indexes are better.