An Outlier Detection Method of GNSS/SINS Integrated Navigation Based on Accelerometer Bias Stability
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摘要: 在地面车载组合导航中，全球导航卫星系统（global navigation satellite system，GNSS）的观测值容易受地面复杂环境的干扰，导致其定位结果出现异常，严重影响GNSS/捷联惯性导航系统（strap-down inertial navigation system，SINS）组合的滤波解算。从惯导系统误差特性的角度，研究了一种基于加表零偏稳定性的组合导航异常探测新方法。该方法从加表零偏解算的异常来发现GNSS位置、速度等观测值中的粗差，并采取剔除和降权的抗差方法抵御粗差影响。通过一组车载数据的分析表明，观测粗差对加表零偏解算的影响十分显著，以此为判别条件能够准确地发现观测粗差。采用该方法后，位置误差、速度误差和姿态误差的均方根分别减小了70.8%、87.9%和77.7%，显著提高了组合导航的解算精度和鲁棒性，为组合导航数据的抗差处理提供了一种新思路。Abstract: In the ground vehicle integrated navigation, GNSS observations are often interfered by complex ground environment and thus, its positioning result is more prone to contain outliers which can seriously affect GNSS/SINS integrated filter solution. This paper, from the perspective of IMU system error feature, studies an outlier detection method of GNSS/SINS integrated navigation based on accelerometer bias stability. According to the outlier of accelerometer bias result, the method detects gross errors in GNSS position, velocity, etc; and then applies the robust strategies of rejection and weight reduction to resist the influence of gross errors. The method is analyzed by a set of vehicle measured data. The results show that the observation outliers can greatly affect the accelerometer bias result and thus taking the accelerometer bias stability as a condition, the outliers can be exactly detected. In every direction of ENU, the RMS of position and the RMS of velocity are improved by 70.8% and 87.9% respectively; the RMS of attitude is improved by 77.7%. The method greatly improves the accuracy and robustness of integrated navigation results and provides a new strategy for robust processing of integrated navigation data.
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图 3 不同型号IMU加表零偏稳定性对比
Figure 3. Accelerometer Bias Stability Comparison of Different Types of IMUs
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图 6 卫星数、PDOP值以及双差模糊度固定情况
Figure 6. Satellite Numbers, PDOP Values and Double-Difference Ambiguities Fixed Status
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图 7 3种方法的松组合导航解误差
Figure 7. Navigation Errors of Loosely Coupled Integration Using the Three Algorithms
表 1 不同型号IMU的主要性能指标
Table 1 Main Technical Specifications of Different Types of IMU
性能指标 Ellipse-N SPAN-CPT SPAN-FSAS POS830 陀螺零偏/(°·h-1) 60 20 0.75 0.10 陀螺零偏稳定性 0.2°/s 1.0°/h 0.1°/h 0.01°/h 加表零偏/mg 100 50 1 0.5 加表零偏稳定性/mg 5.0 0.75 0.01 0.005 
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表 2 3种算法RMS对比
Table 2 RMS Comparison of the Three Algorithms
算法 位置误差/m 速度误差/(m·s-1) 姿态误差/(°) 东向 北向 天向 东向 北向 天向 航向角 俯仰角 横滚角 EKF 7.972 3.270 5.863 0.360 0.115 0.272 0.193 0.029 0.059 IGG3 1.463 1.825 0.998 0.061 0.018 0.034 0.036 0.009 0.014 Acc-Bias 1.247 1.836 0.937 0.038 0.021 0.020 0.027 0.008 0.015
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