复杂城市环境下的全球导航卫星系统/捷联惯性导航系统组合导航算法

Global Navigation Satellite System/Strapdown Inertial Navigation System Integrated Navigation Algorithm in Complex Urban Environment

针对复杂城市环境下,全球导航卫星系统(GNSS)信号出现频繁短暂失锁或拒止时,对GNSS/捷联惯性导航系统(SINS)组合导航系统的导航精度和鲁棒性影响较大问题,该文提出一种改进的因子图滤波方法。首先使用GNSS接收机内部参数构建信号误差鉴别函数,能实时估计出信号受多径干扰、遮挡等情况下的信号测量性能;同时利用载体运动约束条件构造零速修正因子,对GNSS拒止情况下的系统状态进行更新,避免系统导航性能极速下降。实验结果表明,改进的因子图方法相比经典因子图方法,在城市复杂环境下能提高定位精度63.50%和测速精度42.26%,同时也具有更低的存储量和计算复杂度,特别适用于城市车辆辅助驾驶导航设备中,对导航精度、硬件资源和实时性约束强的场景。

In order to solve the problem that the Global Navigation Satellite System(GNSS)signal is frequently unlocked or rejected in complex urban environment,which has great influence on the navigation accuracy and robustness of GNSS/Strapdown Inertial Navigation System(SINS)integrated navigation system,an improved factor graph filtering method is proposed in this paper.Firstly,GNSS receiver internal parameters are used to construct signal error identification function to estimate the performance of signal measurement at real time in the situation of multipath interference and occlusion.Simultaneously,zero-velocity update factor is constructed by the carrier motion constraint to update the system state under the condition of GNSS rejection.The experimental results show that compared with the classical factor graph method,the improved factor graph method can improve the positioning accuracy by 63.50%and the velocity measurement accuracy by 42.26%in complex environment with lower storage and computational complexity.The method is especially suitable for the scenarios with strong constraints on navigation accuracy,hardware resources and real-time performance in urban vehicle assisted driving navigation equipment.