The invention discloses a ship target 6D pose estimation method based on point cloud data, and the method comprises the steps: 1, obtaining a ship point cloud data set of an offshore scene, and enabling a data set label to comprise a target type, the three-dimensional coordinates of a target, the three-dimensional size of the target, and the three-dimensional pose of the target; 2, constructing aneural network, and performing point-by-point point cloud feature extraction by adopting Point Net + + to obtain point-by-point high-dimensional features; 3, generating a 3D bounding box proposal frombottom to top, a real segmentation mask is generated based on the 3D bounding box, foreground points are segmented, and meanwhile the bounding box proposal with angle information is generated from the segmentation points and used for RCNN input; and 4, performing proposal optimization based on the proposal obtained in the step 3, the foreground segmentation features and the spatial features so asto output final classification, a 3D frame and an attitude angle. According to the method, the pose estimation effect of the three-dimensional target is achieved in an end-to-end learning mode, and the real-time performance of pose estimation is improved.