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Dynamically Adjusting Filter Gain Method for Suppressing GNSS Observation Outliers in Integrated Navigation

文献类型： 外文期刊

作者： Wang, Lihui 1 ; Zhi, Kangyi 2 ; Li, Bin 3 ; Zhang, Yuexin 1 ;

作者机构： 1.Southeast Univ, Sch Instrument Sci & Engn, Minist Educ, Key Lab Microinertial Instrument & Adv Nav Techno, Nanjing 210096, Jiangsu, Peoples R China

2.Beijing Inst Control Engn, Beijing 100081, Peoples R China

3.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

关键词： GNSS/INS Integrated Navigation; Outliers Processing; Innovation Vector; chi(2)-test; Filter Gain

期刊名称：JOURNAL OF NAVIGATION （ 影响因子：1.995； 五年影响因子：2.277 ）

ISSN： 0373-4633

年卷期： 2018 年 71 卷 6 期

页码：

收录情况： SCI

摘要： Global Navigation Satellite Systems (GNSSs) are easily influenced by the external environment. Signals may be lost or become abnormal thereby causing outliers. The filter gain of the standard Kalman filter of a loosely coupled GNSS/inertial navigation system cannot change with the outliers of the GNSS, causing large deviations in the filtering results. In this paper, a method based on a chi(2)-test and a dynamically adjusting filter gain method are proposed to detect and separately to suppress GNSS observation outliers in integrated navigation. An indicator of an innovation vector is constructed, and a chi(2)-test is performed for this indicator. If it fails the test, the corresponding observation value is considered as an outlier. A scale factor is constructed according to this outlier, which is then used to lower the filter gain dynamically to decrease the influence of outliers. The simulation results demonstrate that the observation outlier processing method does not affect the normal values under normal circumstances; it can also discriminate between single and continuous outliers without errors or omissions. The impact time of outliers is greatly reduced, and the system performance is improved by more than 90%. Experimental results indicate that the proposed methods are effective in suppressing GNSS observation outliers in integrated navigation.

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