| Combined Method of Datum Transformation Between Different Coordinate Systems |
| |
| 作者姓名： | 王晓妮 张洁 |
| |
| 作者单位： | Xi'an Research Institute of Surveying and Mapping,1 Middle Yanta Road,Xi'an 710054,China
|
| |
| 基金项目： | ProjectsupportedbytheNaturalScienceFoundationofChina (4982 51 0 7)，andpartlysupportedbytheNationalClimbingProgramofChinaaswellastheScientif icResearchFoundationfortheReturnedOverseasChineseScholars，MinistryofEducation. |
| |
| 摘 要： | The similarity transformation model between different coordinate systems is not accurate enough to describe the discrepancy of them.Therefore,the coordinate transformation from the coordinate frame with poor accuracy to that with high accuracy caanot guarantee a high precision of transformation.In this paper,a combined method of similarity tranformation and regressive approximating is presented.The local error accumulation and distortion are taken into consideration and the precision of coordinate system is improved by using the recommended method.
|
| 关 键 词： | 坐标系 相似变换 回归模拟 卫星激光测距 GPS 全球定位系统 甚长基线干涉测量 定位精度 |
Combined method of datum transformation between different coordinate systems |
| |
| Yang Yuanxi,Xu Tianhe.Combined Method of Datum Transformation Between Different Coordinate Systems[J].Geo-Spatial Information Science,2002,5(4):5-9. |
| |
| Authors: | Yang Yuanxi Xu Tianhe |
| |
| Institution: | YANG Yuanxi XU Tianhe |
| |
| Abstract: | The similarity transformation model between different coordinate systems is not accurate enough to describe the discrepancy of them.Therefore,the coordinate transformation from the coordinate frame with poor accuracy to that with high accuracy cannot guarantee a high precision of transformation.In this paper,a combined method of similarity transformation and regressive approximating is presented.The local error accumulation and distortion are taken into consideration and the precision of coordinate system is improved by using the recommended method |
| |
| Keywords: | coordinate transformation similarity transformation regressive approximating |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
