惯性/卫星/里程计多信息融合方法及在铁路测绘中的应用

针对基于惯性技术对铁路基础设施进行精确测绘的需求提出一种多信息融合惯性基准方案,为测量测绘提供高精度位置和姿态参考。对载体运动特点和车载状态下惯性/里程组合导航航向角误差可观性进行分析,认为天向陀螺漂移和航向误差是导致测量精度下降的主要因素,针对该问题设计了基于双向滤波、双向平滑的多信息融合方案,针对缺乏绝对位置基准的应用情况,引入"正矢"概念和相对定位精度的评判方法。仿真及试验结果表明,在陀螺常值漂移0.2(°)/h条件下,该方案相对定位精度优于0.3 mm(300 m弦正矢),显著提高了车载铁路线路测绘位置、姿态基准精度,降低了对惯性器件的要求,利用中、低精度器件实现了高精度测量定位。

Multi-information fusion method of INS/Odometer/GNSS and its application in railway surveying and mapping

According to the demand for accurate mapping the railway infrastructure based on the inertial technology,a multi-information fusion scheme is put forward which can provide high-precision attitude and position as the surveying and mapping references.The characteristics of high-speed train motion and the heading error's observability of the inertial/odometer integrated navigation system are analyzed,which show that the main factors that affect the measurement accuracy are the Y-gyro drift and the heading accuracy.A multi-information fusion scheme is designed based on the forward/reverse filtering/smoothing track fusion,and the concept of "vector" is introduced to judge the relative positioning precision.Simulation and test results show that the proposed scheme can significantly increases the precisions of attitude and position references in railway surveying and mapping and realize high-precision measurement and positioning by low-and mid-precision inertial devices,in which the relative positioning error can be reduced to ＜0.3 mm (300 m versine vector) even when the gyro's constant drift is increased by 0.2 (°)/h.