测绘学报 ›› 2019, Vol. 48 ›› Issue (1): 9-17.doi: 10.11947/j.AGCS.2019.20170367

• 大地测量学与导航 • 上一篇    下一篇

组合粗差探测的MHSS ARAIM算法

张亚彬1,2,3, 王利1,2,3, 范丽红1,2,3, 曲轩宇1,2,3   

  1. 1. 长安大学地质工程与测绘学院, 陕西 西安 710054;
    2. 地理信息工程国家重点实验室, 陕西 西安 710054;
    3. 地理国情监测国家测绘地理信息局工程技术研究中心, 陕西 西安 710054
  • 收稿日期:2017-07-05 修回日期:2018-09-15 出版日期:2019-01-20 发布日期:2019-01-31
  • 通讯作者: 王利 E-mail:wangli@chd.edu.cn
  • 作者简介:张亚彬(1992-),男,硕士生,研究方向为接收机自主完好性监测算法及应用。E-mail:zyb199202@126.com
  • 基金资助:

    国家自然科学基金(41304033;41504006;41604001);中国第二代卫星导航系统重大专项(GFZX301040308);地理信息工程国家重点实验室开放研究基金(SKLGIE2017-Z-2-1);中央高校基本科研业务费专项(310826172006;310826172202;310826173101)

MHSS ARAIM algorithm combined with gross error detection

ZHANG Yabin1,2,3, WANG Li1,2,3, FAN Lihong1,2,3, QU Xuanyu1,2,3   

  1. 1. College of Geology Engineering and Geomantics, Chang'an University, Xi'an 710054, China;
    2. State Key Laboratory of Geographic Information Engineering, Xi'an 710054, China;
    3. National Administration of Surveying, Mapping and Geoinformation Engineering Research Center of Geographic National Conditions Monitoring, Xi'an 710054, China
  • Received:2017-07-05 Revised:2018-09-15 Online:2019-01-20 Published:2019-01-31
  • Supported by:

    The National Natural Science Foundation of China (Nos. 41304033;41504006;41604001);The Grand Projects of the BeiDou-2 System(No. GFZX0301040308);The Foundation of State Key Laboratory of Geo-information Engineering (No. SKLGIE2017-Z-2-1);The Fundamental Research Funds for the Central Universities(Nos. 310826172006;310826172202;310826173101)

摘要:

针对目前MHSS ARAIM(multiple hypothesis solution separation advanced receiver autonomous integrity monitoring)算法存在的抗差能力弱、计算子集过多、计算量过大等不足,提出一种组合粗差探测的MHSS ARAIM算法。该算法先用粗差探测方法对原始数据进行粗差识别与剔除,而后用MHSS ARAIM算法处理经粗差探测后的数据,可弥补MHSS ARAIM算法的不足。对若干IGS和全球连续监测评估系统iGMAS(international GNSS monitoring and assessment system)监测站观测数据进行计算和分析。结果表明:在航行LPV-200阶段,该算法应用于GPS和BDS导航的性能优于MHSS ARAIM;在假设单故障情况下,该算法对GPS和BDS观测数据的有效监视门限EMT(effective monitor threshold)的精度分别提高了22.47%和9.63%,对VPL(vertical protection level)的精度分别提高了32.28%和12.98%;在假设双故障情况下,对EMT的精度分别提高了80.85%和29.88%,对VPL的精度分别提高了49.66%和18.24%。

关键词: 粗差探测, ARAIM, 故障检测和识别, MHSS ARAIM

Abstract:

Because there are some shortcomings in the current MHSS ARAIM algorithm, such as the weaker robustness, too many computational subsets and large amount of computation, a multiple hypothesis solution separation advanced receiver autonomous integrity monitoring (MHSS ARAIM) algorithm combined with gross error detection is proposed in this paper. With this new algorithm, the gross error detection method is used to identify and eliminate the gross data in the original data first. Then the MHSS ARAIM algorithm is used to deal with the data after the gross error detection. Therefore, this new algorithm can make up for the weakness of the MHSS ARAIM algorithm. Through the data processing and analysis from several IGS and international GNSS monitoring and assessment system (iGMAS) stations, the results show that this new algorithm is superior to MHSS ARAIM in the aviation phase of LPV-200 when it is used in the navigation with GPS and BDS. And under the assumption of a faulty satellite, accuracy of the effective monitoring threshold (EMT) is improved about 22.47% and 9.63%, and accuracy of the vertical protection level (VPL) is improved about 32.28% and 12.98%respectively for GPS and BDS observations respectively. Moreover,under the assumption of two faulty satellites, accuracy of the EMT is improved about 80.85% and 29.88%, and accuracy of the VPL is improved about 49.66% and 18.24% for GPS and BDS observations respectively.

Key words: gross error detection, ARAIM, fault detection and identification, MHSS ARAIM

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