Small viewing field of the solid-state LiDAR makes loop closure detection difficult. Therefore, a loop closure detection method based on single frame-submap descriptor matching is proposed. First, to obtain a submap with the pose provided by the front-end odometry, several frames of point clouds are spliced, then the descriptors of the submap are obtained, and their positions are added to the KD tree. Second, for each current frame, the KD tree is used to search candidate submaps, and the descriptor is obtained after projecting to the submap coordinate system according to the pose getting from odometry, so as to realize the rotation and translation invariance of the descriptor. Then, the binary descriptor is used for alignment, and the mask method is used to calculate the similarity between the current frame descriptor and the submap descriptor. Finally, the CFB-ICP algorithm is used to register the qualified loop closure pairs to obtain the loop closure factors, and factor graph optimization is carried out. Experimental tests are carried out in open source data sets and real outdoor environments. The results show that the algorithm can reduce the cumulative error under long-distance operations and improve the accuracy of positioning and mapping under the premise of satisfying real-time performance.