井下多传感器组合导航系统

Underground multi-sensor integrated navigation system

  • 摘要: 针对井下车辆高精度惯性导航成本较高、低成本MEMS惯性传感器漂移较大等问题,提出一种井下多传感器组合导航系统,该系统通过蓝牙测距信息、MEMS惯性传感器及车载里程计信息进行组合导航。利用卡尔曼滤波技术融合多传感器数据,结合蓝牙测距信息抑制MEMS惯性传感器漂移,提高车载惯性传感器在一段时间内的定位精度;通过MEMS惯性传感器预测车辆位置,有效滤除干扰标签的蓝牙信号,提高数据可靠性;融合车辆里程计数据后,定位结果更加稳定可靠。测试结果表明,在井下蓝牙标签间隔10 m布站情况下,每10 m定位误差在3.2 m以内,能够满足井下导航要求。

     

    Abstract: In view of problems of high cost of high-precision inertial navigation of underground vehicle and large drift of low-cost MEMS inertial sensor, an underground multi-sensor integrated navigation system was proposed, which uses bluetooth ranging information, MEMS inertial sensor and vehicle odometer information for integrated navigation. The system uses Kalman filter technology to fuse multi-sensor data, combines Bluetooth ranging information to suppress MEMS inertial sensor drift, and improve positioning accuracy of inertial sensor in a period of time; Vehicle position is predicted by MEMS inertial sensor to effectively filter out Bluetooth signal of interference tags, so as to improves data reliability; Integration of odometer data can make the positioning result more stable and reliable. The test results show that the positioning error of every 10 m is less than 3.2 m under the condition that the underground Bluetooth tags are distributed 10 m apart, which can meet requirements of underground navigation.

     

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