先验信息约束的车载GNSS RTK/IMU紧组合导航算法

GNSS RTK/IMU tightly coupled integration algorithm with prior information constraint for vehicle navigation

针对传统RTK/IMU组合导航系统在复杂环境中的模糊度固定率低导致其精度和可靠性较差的问题,文中提出一种先验信息约束的车载GNSS RTK/IMU紧组合导航算法。该算法首先构建一种基于IMU辅助伪距一致性检测的GNSS质量控制模型,以识别并剔除粗差较大的伪距观测量,接着提出一种附加先验长度信息约束的GNSS模糊度解算方法,提高GNSS模糊度解算的成功率,最后,将RTK与IMU输出的数据通过EKF进行紧组合滤波融合,从而提高组合导航系统在复杂环境中的精度与可靠性。实测车辆实验数据表明,提出算法相对于传统RTK/IMU紧组合导航算法,在三维位置和速度上的精度提升率达到36.36%和14.29%;与基于IMU位置信息约束的RTK/IMU紧组合导航算法相比,提升率分别达到26.31%和20.00%。

To solve the problem of poor accuracy and reliability of traditional RTK/IMU integrated system in complex environments due to the low success rate of ambiguity resolution,this paper proposes a RTK/IMU tightly coupled vehicle navigation algorithm with prior information constraints.First,the accurate position information output by IMU mechanization is used to assist the GNSS quality control process to identify and eliminate the pseudoranges with large errors.Then,a new GNSS ambiguity solving method with prior length constraint is introduced to improve the success rate of ambiguity resolution.Finally,a tightly coupled integration scheme based on EKF is constructed to fuse the data output from both RTK and IMU to improve the accuracy and reliability of the integrated navigation system in complex environments.Results from an onboard vehicle experiment have showed that compared with the conventional RTK/IMU tightly coupled algorithm,the position and velocity accuracy improvements reach 36.36%and 14.29%.Compared with the RTK/IMU tightly coupled algorithm with the IMU position constraint,the improvements reach 26.31%and 20.00%,respectively.