文章基本信息

标题：Adjustment of leveling network by information spread estimation
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作者：Wang Xinzhou
期刊名称：Geo-spatial Information Science
印刷版ISSN：1009-5020
电子版ISSN：1993-5153
出版年度：2001
卷号：4
期号：1
页码：1-4
DOI：10.1007/BF02826628
出版社：Taylor and Francis Ltd
摘要：In practical parameter estimation, we have always chosen either Least Squares Estimation(LSE) or Robust Estimation. Since the distribution of observations is unknown, to select a correct estimation method is very difficult. It is well known that if observations include gross errors, the result of LSE will be badly containinated. On the other hand, if observations do not include any gross errors, the result of robust estimation is not as good as that of LSE. To solve this problem, Wang (1999) developed an estimation method called Information Spread Estimation (ISE) based on the information spread principle. The ISE is a very good method for estimating one parameter which is very robust. However, most of instances in surveying data processing are multi-parameters' estimation, owing to the inherent restrictions of ISE, it can not be applied to the surveying data processing directly. To apply the good method to the field of surveying data processing widely, the author has done the research deeply. This paper applies ISE successfully to the adjustment of leveling network by using the specialties of leveling.
关键词：residual error; data snooping; robust estimation; mean square of weight