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排序对模糊度解算中降相关性能的影响分析
引用本文:鲁铁定,汪 鑫,卢立果,徐兆祥.
排序对模糊度解算中降相关性能的影响分析[J].大地测量与地球动力学,2020,40(5):470-475.
作者姓名:鲁铁定  汪 鑫  卢立果  徐兆祥
作者单位:东华理工大学测绘工程学院;西安测绘研究所;地理信息工程国家重点实验室;长沙市规划勘测设计研究院
基金项目:国家自然科学基金(41804020,41464001);江西省科技落地计划(KJLD12077);国家重点研发计划(2016YFB0501405,2016YFB0502601-04);江西省自然科学基金(2017BAB203032);轨道交通工程信息化国家重点实验室(中铁一院)开放基金(SKLK19-11)。
摘    要:针对不同排序算法对模糊度解算存在降相关性能影响的问题,从理论上分析了自然升序法、对称旋转法及扰动升序法的降相关原理,并基于模拟数据和实测数据,从降相关时间、搜索时间、总体耗时、Bootstrapping成功率及条件数5个方面对3种算法进行对比分析。结果表明,降相关效率与搜索椭球压缩程度呈负相关关系,搜索椭球压缩程度越高,降相关效率越低;对于不同的排序算法,提高降相关性能的关键在于减少降相关时间及对条件方差按一定方向排序,进而提高搜索效率。

关 键 词:模糊度解算  降相关  整数高斯变换  排序  Cholesky分解  

Analysis of the Influence of Sorting on Decorrelation Performance in the Ambiguity Solution
LU Tieding,WANG Xin,LU Liguo,XU Zhaoxiang.Analysis of the Influence of Sorting on Decorrelation Performance in the Ambiguity Solution[J].Journal of Geodesy and Geodynamics,2020,40(5):470-475.
Authors:LU Tieding  WANG Xin  LU Liguo  XU Zhaoxiang
Institution:(Faculty of Geomatics,East China University of Technology,418 Guanglan Road,Nanchang 330013,China;Xi’an Research Institute of Surveying and Mapping,1 Mid-Yanta Road,Xi’an 710054,China;State Key Laboratory of Geo-Information Engineering,1 Mid-Yanta Road,Xi’an 710054,China;Changsha Planning&Design Survey Research Institute,165 Mid-Shuguang Road,Changsha 410000,China)
Abstract:To determine the influence of different sorting algorithms on the decorrelation performance of ambiguity in the ambiguity resolution, we theoretically analyze the natural ascending sorting method, the sorted QR decomposition method and the perturbed ascending sorting strategy. Secondly, based on simulated data and measured data, we compare and analyze the three algorithms in five aspects: decorrelation time, search time, overall time consumption, bootstrapping success rate, and condition number. The results show that decorrelation efficiency is negatively correlated with the degree of compression of the search ellipsoid. The higher the degree of compression of the search ellipsoid, the lower the decorrelation efficiency. For different sorting algorithms, the key to improve decorrelation performance is to reduce the decorrelation time and conditional variances are ordered in a certain direction to improve search efficiency.
Keywords:ambiguity solution  decorrelation  integer Gauss transformation  sorting  Cholesky decomposition  
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