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| 引用本文： | 胡川,陈义,彭友.??????????С???????????[J].大地测量与地球动力学,2013,33(4):56-60. |
| 作者姓名： | 胡川 陈义 彭友 |
| 作者单位： | 1. 同济大学测绘与地理信息学院,上海,200092 2. 同济大学测绘与地理信息学院,上海200092 ;现代工程测量国家测绘局重点实验室,上海200092 3. 四川建筑职业技术学院工程管理系,德阳,618000 |
| 摘 要： | ???????????????????к?????????????????к??????????????????????С????????????????????????????????????С?????????????????????????С?????????????????????????С?????????????????????????????????????????????????????????????????С?????????з???????????????????????????????????????????С?????????????????????????????к?????????????????????????????????????????????????λ????????????????????????λ?????????????????????????????????????з?????????????????????????????????????????,??????????С??????????????????λ??????????????????????????? |
| 关 键 词： | ??????С????? ?????С???? ??????С????? ??????????С????? ???????? |
ON MIXED STRUCTURED TOTAL LEAST SQUARES FOR PARAMETERS ESTIMATION |
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| Hu Chuan;Chen Yi;Peng You.ON MIXED STRUCTURED TOTAL LEAST SQUARES FOR PARAMETERS ESTIMATION[J].Journal of Geodesy and Geodynamics,2013,33(4):56-60. | |
| Authors: | Hu Chuan;Chen Yi;Peng You |
| Institution: | Hu Chuan;Chen Yi;Peng You;College of Surveying and Geo-informatics,Tongji University;Key Laboratory of Modern Engineering Surveying,SBSM;Department of Engineering Management,SCCAT; |
| Abstract: | ??In this contributions we defined the model of mixed structured total least squares according to the mixed least squares??total least squares and proposed an iterative algorithm for the mixed structured total least squares problems, which solving by the nonlinear least squares adjustment theory. Three numerical examples are given at last,where assumes the errors of elements in observation vector equal ,greater and lesss than the error of independent elements in coefficient matrix ,respectively. It’s shown that the method represented in this paper would be able to estimate the parameters theoretically closer to the true value and attain the more precise mean square error of weight unit than least squares and mixed least squares??total least squares, especially when the coefficient matrix which holds more errors than observation vector. |
| Keywords: | total least squares mixed least squares-total least squares mixed structured total least squares parameters estimation |
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