Detection and Exclusion of Abnormal Measurement Data in GNSS Precise Point Positioning
Detection and Exclusion of Abnormal Measurement Data in GNSS Precise Point Positioning
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GNSS精密单点定位中异常测量数据的检测与排除
DOI：
10.5687/sss.2012.119
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
S. Sugimoto
中科院分区：
文献类型：
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作者：
A. Chabata;M. Kamimura;Y. Kubo;S. Sugimoto
本文提出了一种基于GR（GNSS Regressive）模型的RTK-PPP（真实的实时动态精密单点定位）中GNSS（global navigation satellite system）观测数据周跳和多径异常检测方法。在对GNSS卫星接收信号进行周跳和多径检测后，剔除多径伪橙数据，重新估计L1或L2载波相位中包含的周跳整周模糊度，以保持GNSS定位精度。本文提出了两种探测周跳的方法。第一种方法是基于创新过程的统计测试，第二种方法是使用整周模糊度的连续时间估计之间的差，并应用卡尔曼滤波器。最后，我们给出了使用真实的GPS观测量在汽车上的实验结果，并证明了我们的方法检测周跳和多径的可行性。
In this paper, we present a method of detecting abnormal measurement data due to cycle slips and multipath in GNSS (global navigation satellite system) for RTK-PPP (real time kinematic precise point positioning), based on GR (GNSS Regressive) models. After detecting the received signals with cycle slips and multipath from the GNSS satellites, we exclude psuedoranges data for multipath and re-estimate the integer ambiguity included in L1 or L2 carrier phase for cycle slips, for maintaining the accuracy of GNSS positioning. We present two methods of detecting cycle slips. The first method is based on statistical testing of the innovation process and the second method is using difference between successive-time estimates of integer ambiguities, with applying the Kalman filter. Finally we present the experimental results using real GPS observables in the automobile and show the feasibility of detecting cycle slips and multipath by our method proposed in this paper.
GNSS 回归模型和精确单点定位
DOI：
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发表时间：
2005
期刊：
Proc.of the 36th ISICE Int.Symp.on Stochastic Systems Theory and Its Applications
影响因子：
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作者：
S.Sugimoto;Y.Kubo
通讯作者：
Y.Kubo
基于GNSS回归方程的单点定位和相对定位的统一方法
DOI：
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发表时间：
2006
期刊：
Proc.19th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS 2006)
影响因子：
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作者：
S.Sugimoto;Y.Kubo
通讯作者：
Y.Kubo