基于伪距残差和新息的GNSS/IMU抗差自适应定位算法

Robust adaptive position algorithm for GNSS/IMU based on pseudorange residual and innovation

在全球导航卫星系统(GNSS)和惯性测量元件(IMU)组合导航系统中,抗差滤波和自适应滤波常被用于提高组合导航的定位精度。但是抗差滤波和自适应滤波所适用的条件不同,使用不当反而可能会降低组合导航的定位精度,针对此问题,提出基于伪距残差和新息的GNSS/IMU抗差自适应定位算法。所提算法基于伪距残差评估GNSS的定位质量,选择合适的滤波算法进行GNSS/IMU组合导航解算。在长时间GNSS定位质量较差时,基于新息和伪距残差判断是否IMU运动学推算误差大于GNSS观测值误差,从而根据判断的结果选择是否采用抗差因子。结果表明:所提算法相对于扩展卡尔曼滤波算法在东、北和天方向上分别提高36.05%、22.71%和56.22%的定位精度。

Algorithms of robust filtering and adaptive filtering are commonly used to improve the positioning accuracy of the navigation system integrating global navigation satellite system(GNSS)and inertial measurement units(IMU).However,the conditions applicable to robust filtering and adaptive filtering are different,and improper use of the filter may reduce the positioning accuracy of the integrated system.To solve this problem,a robust adaptive position algorithm for GNSS/IMU is proposed based on pseudorange residual and innovation.The positioning quality of GNSS is evaluated based on pseudorange residuals.The appropriate filtering algorithm is selected to solve the GNSS/IMU integrated navigation.Innovation and pseudorange residuals are then used to determine whether the IMU kinematic estimation error is greater than the GNSS observation error in long-time low quality GNSS.The robust factor is used based on the determined results.Experimental results show that the positioning accuracy of the proposed algorithm is improved by 36.05%,22.71%,and 56.22%in the east,north and up directions,respectively,compared with the results from the extended Kalman filter algorithm.