首页> 外文会议>Proceedings of the Institute of Navigation 2010 international technical meeting (ITM 2010) >Accurate Pipeline Surveying Using Two-Filter Optimal Smoothing of Inertial Navigation Data Augmented with Velocity and Coordinate Updates
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Accurate Pipeline Surveying Using Two-Filter Optimal Smoothing of Inertial Navigation Data Augmented with Velocity and Coordinate Updates

机译:使用对速度和坐标更新增强的惯性导航数据进行二次滤波最佳平滑的精确管道测量

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摘要

Pipelines are constructed to transport or dispose liquid and gases, commonly operated by oil, gas, sewerage and chemical industries. The pipeline system consists of three basic components namely gathering lines, trunk lines and distribution lines. Environmental, safety and economic concerns necessitate the constant monitoring of pipelines to avoid potentially hazardous failures. Currently, Pipeline Inspection Gauges (PIGs) can be sent through the pipelines to monitor the inside conditions. The Inertial Navigation System (INS) is employed to conduct the overall PIG navigation due to the unavailability of GPS signals inside the pipeline. Due to the time-dependent errors of INS only navigation, additional aiding sensors and/or auxiliary velocity and position updates need to be used to compensate for such errors. In addition, optimal smoothing methods are required since optimal smoothing is a post-mission estimator that provides the optimal estimates by using all available measurements. In this paper, two smoothers, namely Two-Filter Smoother (TFS) and the Rauch-Tung-Striebel Smoother (RTSS) will be implemented based on an Extended Kalman Filter (EKF). Using real pipeline inertial data collected with a tacticalgrade Inertial Measuring Unit (IMU), the effect of the additional velocity updates and available position updates will be shown. Moreover, the performance of both optimal smoothers will be evaluated. The combined implementation of the additional filter updates and smoothing demonstrated a remarkable improvement in the navigation accuracy compared to the original KF solution.
机译:管道用于运输或处理通常由石油,天然气,污水处理和化学工业运营的液体和气体。管道系统由三个基本组件组成,即集水线,干线和配电线。出于环境,安全和经济方面的考虑,必须对管道进行持续监控,以避免潜在的危险故障。当前,可以通过管道发送管道检查规(PIG)来监视内部条件。由于管道内GPS信号不可用,惯性导航系统(INS)用于进行整体PIG导航。由于仅INS的时间相关误差,需要使用附加的辅助传感器和/或辅助速度和位置更新来补偿此类误差。另外,需要最佳平滑方法,因为最佳平滑是任务后估计器,其通过使用所有可用测量来提供最佳估计。在本文中,将基于扩展卡尔曼滤波器(EKF)来实现两个平滑器,即“两个过滤器平滑器”(TFS)和“劳赫-通-斯特里贝尔平滑器”(RTSS)。使用战术级惯性测量单元(IMU)收集的实际管道惯性数据,将显示附加速度更新和可用位置更新的效果。此外,将评估两个最佳平滑器的性能。与原始KF解决方案相比,附加滤波器更新和平滑处理的组合实施证明了导航精度的显着提高。

著录项

  • 来源
  • 会议地点 San Diego CA(US);San Diego CA(US)
  • 作者单位

    Mobile Multi-Sensor Systems (MMSS) Research Group,Department of Geomatics Engineering, the University of Calgary, Calgary, Alberta, CANADA;

    Mobile Multi-Sensor Systems (MMSS) Research Group,Department of Geomatics Engineering, the University of Calgary, Calgary, Alberta, CANADA;

    Mobile Multi-Sensor Systems (MMSS) Research Group,Department of Geomatics Engineering, the University of Calgary, Calgary, Alberta, CANADA;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电导航;
  • 关键词

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