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3D reconstruction technology is becoming a key tool for obtaining comprehensive, complete and accurate information about drainage pipes. The actual inspection is limited by such factors as pipe blockage and pipe inspection protocols, resulting in different positions, partial overlaps or gaps in the obtained sonar point cloud model, and the need to obtain a complete pipe model through alignment. At the same time, the traditional ICP algorithm has the problems of low efficiency and poor accuracy for the pipeline model. Therefore, this paper proposes a point cloud alignment algorithm that combines coarse alignment based on feature point matching with improved ICP fine alignment. Firstly, the ISS feature point detection method is used to detect the model feature points, and the feature points are further described by the FPFH; secondly, the RANSAC algorithm is used to filter the correct feature matching point set, and the initial transformation parameters are solved by the quadratic method to complete the coarse alignment; finally, based on the coarse alignment, the ICP algorithm with improved nearest corresponding point query is used to complete the fine alignment. The experimental results demonstrate the feasibility and superiority of the algorithm, which can provide a high-precision point cloud data model for the subsequent detection of tunnel defects.