抗差估计在RTK/INS紧组合中的应用研究
Application of robust estimation in RTK/INS tightly-coupled algorithms
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摘要: 针对动态环境下GNSS/INS导航定位结果常受粗差影响的问题,提出了一种基于抗差卡尔曼滤波的GPS/BDS双系统RTK/INS紧组合导航定位算法,根据方差膨胀模型,建立抗差卡尔曼算法,得到GNSS/INS紧组合抗差解,并通过两个不同区域的实测车载实验进行了算法验证. 实验结果表明:本方法相较于传统方法,在N、E、D三个方向的导航精度分别提高1.4~4.6 cm,0.7~9 cm,1.5~2 cm,模糊度固定成功率提高10.3%~25.6%,导航精度及可靠性得到显著提高,对动态环境下车载或自动驾驶等应用具有一定的理论参考和实用价值.Abstract: GNSS/INS navigation positioning results for dynamic environment are often affected by the gross error problem, a kind of GPS/BDS double system RTK/INS tightly-couplede integration algorithm based on robust kalman filter is proposed. According to variance expansion model, robust Kalman algorithm is established to obtain GNSS/INS tightly integrated robust solutions, and through two different regions. The experimental results show that the navigation accuracy of this method is improved by 1.4~4.6 cm, 0.7~9 cm, 1.5~2 cm, and the success rate of ambiguity fixing is increased by 10.3~25.6% compared with the traditional methods in three directions of N, E and D, respectively. The navigation accuracy and reliability of this method are improved significantly, and the vehicle navigation accuracy and reliability in dynamic environment are improved. The application of automatic driving has certain theoretical reference and practical value.