Abstract: Because of the angular response effect, a significant imbalance of backscatter strengths always occurs in the multibeam image, which seriously affects the sonar image quality and limits further application of sonar images (for example, seabed target recognition and sediment classification). Current existing methods are mostly based on mathematical interpolation method or acoustic models, but there are still many deficiencies when dealing with complex situations. To solve these problems, this paper proposes a method of weakening angular response effect of the multibeam sonar image based on the angular backscatter characteristics of different seabed sediment type. Firstly, the suitable angular response parameters are reasonably chosen, and the k-mean unsupervised classification method is used to classify the angular response parameters to different sediment types. Secondly, the ave-rage of angular backscatter strength curves corresponding to different seabed sediment type is calcula-ted to obtain the echo characteristic curve of each sediment types. Finally, the angular response effect is weakened by subtracting the echo characteristic curve of each sediment type from the original echo strength curve and adding the average backscatter strength value of each sediment type. Following the steps, the consistency of the echo intensity is achieved and the quality of the sonar image is improved. During the processes, as to the problem of k selection when using the k-mean method, this paper gives out an iterative selection method. In the experiment, the multibeam sonar data measured in the waters of Jiaozhou Bay was used to verify the method, and it was proved that the method can effectively weaken the angular response effect.