發(fā)布時間：2019-06-28 10:49

【摘要】：該文首先介紹了解決層析方程組病態(tài)問題的代數(shù)重構算法,并對影響該算法迭代結果的松弛因子、投影次序、停止規(guī)則進行了討論,提出了基于素數(shù)分解排序的水汽層析代數(shù)重構算法。其次,詳細陳述了該算法的3個核心內容:分組排序、素數(shù)分解排序、非負約束。分組排序可提高反演結果精度;素數(shù)分解排序保證了解的無偏性;非負約束則使迭代結果符合水汽值的非零特性。最后,利用2015年8月13日UTC 0時的香港參考站的觀測數(shù)據(jù)對6組實驗方案進行了分析,證明了基于素數(shù)分解的投影排序對水汽層析結果具有重要影響,且通過該方法可以有效提高代數(shù)重構算法解算GNSS水汽層析方程組的精度。
[Abstract]:In this paper, an algebra reconstruction algorithm for solving ill-conditioned problems of tomographic equations is introduced, and the relaxation factors, projection order and stop rules that affect the iterative results of the algorithm are discussed, and a steam chromatography algebra reconstruction algorithm based on prime number decomposition and sorting is proposed. Secondly, the three core contents of the algorithm are described in detail: grouping sorting, prime decomposition sorting and non-negative constraints. Grouping sorting can improve the accuracy of inversion results, prime decomposition sorting ensures the unbiased solution, and non-negative constraints make the iterative results conform to the non-zero characteristics of water vapor value. Finally, six groups of experimental schemes are analyzed by using the observation data of Hong Kong reference station at UTC 00 on August 13, 2015. It is proved that the projection ranking based on prime decomposition has an important influence on the results of water vapor chromatography, and the accuracy of solving GNSS water vapor chromatography equations can be effectively improved by using this method.
【作者單位】： 中國礦業(yè)大學環(huán)境與測繪學院;
【基金】：國家自然科學基金項目(41504032) 江蘇省自然科學基金項目(BK20150175) 高等學校博士學科點專項科研基金項目(20130095110022)
【分類號】：P228.4;P407

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1 張尊良;GPS三維水汽層析的算法研究與實現(xiàn)[D];中國石油大學(華東);2014年

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本文編號：2507242