测绘学报 ›› 2020, Vol. 49 ›› Issue (8): 955-964.doi: 10.11947/j.AGCS.2020.20190417

• 大地测量学与导航 • 上一篇    下一篇

GNSS模糊度降相关性能的条件方差平稳度评价法

卢立果1,2, 刘万科3, 鲁铁定2, 马立烨4, 吴汤婷2, 杨元喜1   

  1. 1. 西安测绘研究所地理信息工程国家重点实验室, 陕西 西安 710054;
    2. 东华理工大学测绘工程学院, 江西 南昌 330013;
    3. 武汉大学测绘学院, 湖北 武汉 430079;
    4. 武汉大学卫星导航定位技术研究中心, 湖北 武汉 430079
  • 收稿日期:2019-10-12 修回日期:2020-05-26 发布日期:2020-08-25
  • 通讯作者: 刘万科 E-mail:wkliu@sgg.whu.edu.cn
  • 作者简介:卢立果(1989-),男,博士,讲师,研究方向为GNSS模糊度解算。E-mail:lglu66@163.com
  • 基金资助:
    国家自然科学基金(41804020;41774031);国家重点研发计划(2016YFB0501405);江西省自然科学基金(20202BAB212010;20192BAB217011)

Conditional variance stationarity evaluation method for GNSS ambiguity decorrelation

LU Liguo1,2, LIU Wanke3, LU Tieding2, MA Liye4, WU Tangting2, YANG Yuanxi1   

  1. 1. State Key Laboratory of Geo-Information Engineering, Xi'an Research Institute of Surveying and Mapping, Xi'an 710054, China;
    2. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    3. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    4. GNSS Research Center, Wuhan University, Wuhan 430079, China
  • Received:2019-10-12 Revised:2020-05-26 Published:2020-08-25
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41804020;41774031);The National Key Research and Development Program (No. 2016YFB0501405);The Natural Science Foundation of Jiangxi Province of China (Nos. 20202BAB212010;20192BAB217011)

摘要: GNSS模糊度降相关通过整数变换优化条件方差的排列顺序,提高搜索效率。降相关和条件方差的关系及其评价是关键问题之一。针对这一问题,本文从理论上分析了排序后模糊度降相关与条件方差之间的数值关系,发现降相关性能与条件方差数值序列的平稳性有关,降相关性能越强,条件方差数值序列越平稳。基于这一理论关系,给出了“条件方差平稳度”定义,并将其作为评价降相关性能的指标。通过模拟和实测数据验证,并采用条件方差变化趋势图和搜索时间来定性和定量评价降相关性能,用以判定条件方差平稳度的合理性。试验结果表明,条件方差平稳度可以较精确直观地衡量模糊度的降相关性能。本文定义的指标揭示了模糊度降相关的本质。

关键词: GNSS, 模糊度, 降相关, 条件方差, 评价指标

Abstract: GNSS ambiguity decorrelation is to optimize the permutation order of conditional variance by integer transformation, so as to improve the search efficiency. One of the key problems is how to evaluate the relationship between decorrelation and conditional variance. Aiming at this problem, this paper theoretically analyzes the numerical relationship between decorrelation and conditional variance after sorting. It is found that the decorrelation performance is related to the stationarity of the conditional variance sequence. The stronger the decorrelation performance, the more stable the conditional variance sequence. So based on this theoretical basis, the conditional variance stationarity is proposed as an index to evaluate the performance of decorrelation. The results are verified by both simulation and actual test experiments, and the conditional variance trend graph as well as search time are also used to qualitatively and quantitatively evaluate the performance of decorrelation, to determine the rationality of the conditional variance stationarity. The experimental results show that the conditional variance stationarity proposed in this paper can more accurately and intuitively measure the performance of ambiguity decorrelation. The index defined in this paper reveal the essence of GNSS ambiguity decorrelation.

Key words: GNSS, ambiguity, decorrelation, conditional variance, evaluation index

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