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The Performance Evaluation of Gravity and Zero Velocity Measurement Based Field Calibration Methods Applicable for Various Grades of Inertial Sensors

机译:基于重力的性能评估和零速度测量的场校准方法适用于各种惯性传感器

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摘要

Inertial sensors basically composed of accelerometers and gyroscopes are widely used as a crucial part of the navigation systems for various types of civil and military applications. Depending upon the design technologies and manufacturing procedures, inertial sensors contain different types of systematic and stochastic errors in their measurements. The systematic error sources such as bias effect, scaling error, cross-coupling effect of non-sensitive sensor axis measurement etc. result in navigation frame acceleration error, which is double integrated to yield unbounded positioning error to inertial navigated system. In order to reduce the systematic errors built in those sensors, extensive laboratory calibration procedures are well developed with the usage of precision testing equipment such as two or more axis rotation tables, flight motion simulators and precision dividing head equipment. Since the laboratory calibration procedures are essentially depend on rigorous human source, lengthy procedures and highly expensive precision equipment, the idea of inertial sensor calibration without use of precision and costly equipment is adopted in this paper. Based on the previous literature information about the usage of local gravity and zero-velocity measurements for static conditions as a physical quantity is exploited and Extended Kalman Filter based calibration algorithm is developed. Both simulation analysis and real life experiments imply that simple rotation sequences with non-accurate mechanical devices or even with manually via human hand can be used to dictate each of three axis of inertial measurement unit sensor's errors to become observable states. Simulation analysis provides that both of the local gravity measurement and zero-velocity measurement information can be used individually to calibrate both of the accelerometers triad and gyroscopes triad deterministic error terms including repeatable bias errors, scaling errors, cross-coupling errors and g-sensitive bias errors. In this paper, the developed calibration algorithms are tested with near-navigation, tactical and commercial grade inertial measurement units and the performance goal is achieved by comparison with laboratory calibration results.
机译:基本上由加速度计和陀螺仪组成的惯性传感器被广泛用作各种类型的民用和军事应用的导航系统的关键部分。根据设计技术和制造程序,惯性传感器在测量中包含不同类型的系统和随机误差。系统误差源如偏置效果,缩放误差,非敏感传感器轴测量等的交叉耦合效果。导航帧加速度误差,这是双集成的,以产生惯性导航系统的无限定位误差。为了减少这些传感器内置的系统误差,广泛的实验室校准程序是利用精密测试设备的使用,如两个或多个轴旋转桌,飞行运动模拟器和精密分割头设备。由于实验室校准程序基本上取决于严格的人类来源,冗长的程序和高度昂贵的精密设备,因此本文采用了不使用精密和昂贵设备的无需精密和昂贵设备的惯性传感器校准的思想。基于先前关于使用局部重力的使用和零速度测量的静态条件作为物理量的零速度测量的信息,开发了扩展的基于卡尔曼滤波器的校准算法。仿真分析和实际实验均暗示具有非准确机械设备的简单旋转序列或甚至通过人手手动的旋转序列可以用于指示三个惯性测量单元传感器的误差中的每一个变为可观察状态。仿真分析规定,局部重力测量和零速度测量信息都可以单独使用,以校准加速度计三合会和陀螺仪TRIAD确定性误差术语,包括可重复偏置错误,缩放误差,交叉耦合误差和G敏感偏差错误。在本文中,通过近导航,战术和商业级惯性测量单元进行了开发的校准算法,并且通过与实验室校准结果进行比较实现了性能目标。

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