A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D po...A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.展开更多
Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorit...Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.展开更多
文摘A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.
基金supported by National Natural Science Foundation of China (Grant Nos. 41074051, 41021003 and 40874037)
文摘Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.
