A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network
碩士 === 國立中興大學 === 土木工程學系 === 89 === Abstract Basically, densification surveying of control networks can be adjusted by conventional hierarchical adjusted model. It is doubted whether it is reasonable when using conventional hierarchical adjustment model which the known points are assumed...
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ndltd-TW-089NCHU00150932016-07-06T04:10:45Z http://ndltd.ncl.edu.tw/handle/08966459550332506241 A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network 已知點先驗精度對GPS加密網成果精度影響之研究 Tung-Fa Hsieh 謝東發 碩士 國立中興大學 土木工程學系 89 Abstract Basically, densification surveying of control networks can be adjusted by conventional hierarchical adjusted model. It is doubted whether it is reasonable when using conventional hierarchical adjustment model which the known points are assumed errorless for high precision GPS control networks. In this study, two examples of densification networks are used for analysis. One is conventional hierarchical adjustment model, the other is the adjustment model with known points priori precision. We also analyze the calculated results. In the conclusion, it is not reasonable for the densification points precision of GPS densification with conventional hierarchical adjustment model. It will get the average and reasonable densification points precision with the know points priori precision adjustment model. The precision of densification points and baseline are accepted in the rule. Szu-Pyng Kao 高書屏 2001 學位論文 ; thesis 64 zh-TW |
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碩士 === 國立中興大學 === 土木工程學系 === 89 === Abstract
Basically, densification surveying of control networks can be adjusted by conventional hierarchical adjusted model. It is doubted whether it is reasonable when using conventional hierarchical adjustment model which the known points are assumed errorless for high precision GPS control networks.
In this study, two examples of densification networks are used for analysis. One is conventional hierarchical adjustment model, the other is the adjustment model with known points priori precision. We also analyze the calculated results.
In the conclusion, it is not reasonable for the densification points precision of GPS densification with conventional hierarchical adjustment model. It will get the average and reasonable densification points precision with the know points priori precision adjustment model. The precision of densification points and baseline are accepted in the rule.
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Szu-Pyng Kao |
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Szu-Pyng Kao Tung-Fa Hsieh 謝東發 |
author |
Tung-Fa Hsieh 謝東發 |
spellingShingle |
Tung-Fa Hsieh 謝東發 A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
author_sort |
Tung-Fa Hsieh |
title |
A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
title_short |
A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
title_full |
A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
title_fullStr |
A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
title_full_unstemmed |
A Study of the Effect of Known Station’s Priori Variance for a GPS Densification Network |
title_sort |
study of the effect of known station’s priori variance for a gps densification network |
publishDate |
2001 |
url |
http://ndltd.ncl.edu.tw/handle/08966459550332506241 |
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