Graph signal processing is one of the most effective methods to solve irregular data. For this reason, a sparse recovery algorithm based on clustered class graph signals is studied. For complex and irregular array signals, the similar signal atoms are clustered and divided into blocks, the spatial structure of the graph signal is constructed, and the corresponding clustered blocks orthogonal matching pursuit based on graph signal algorithm is designed by using graph filter. In order to verify the effectiveness of the proposed algorithm, a comparative experiment with five algorithms is carried out. Simulation experiments show that the running time of the proposed algorithm is much shorter than other mainstream algorithms under the same sampling rate, and at the same time, the proposed algorithm has a higher peak signal-to-noise ratio at a smaller sampling rate.