Abstract We analyze the application and influence of weighted total least squares method in partial errors-in-variables weight total least squares model (PWTLS), weighted total least squares method(WTLS) and least squares method(LS) in parameters calculation of the three-dimensional coordinate transformation model. Then, we deduce a coordinate transformation method that combines PWTLS and RBF Neural Network. The results show that, when both constant elements and repeated elements exist in the design matrix of coordinate transformation model, unit weighted error and precision of inner coincidence calculated by PWTLS algorithm are better than LS algorithm; in addition, correction of source coordinate calculated by PWTLS is more reasonable than WTLS. The combination method of PWTLS and RBF realizes the practicability of the parameters calculated by PWTLS, which remarkably improves the accuracy of coordinate transformation in practical application.
ZHAO Hui,GUO Chunxi,MENG Jingjuan et al. Three-Dimensional Coordinate Transformation Combined with Weighted Total Least Squares Method and RBF Neural Network[J]. jgg, 2023, 43(1): 29-33.
ZHAO Hui,GUO Chunxi,MENG Jingjuan et al. Three-Dimensional Coordinate Transformation Combined with Weighted Total Least Squares Method and RBF Neural Network[J]. jgg, 2023, 43(1): 29-33.
