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Integration of MEMS Inertial and Pressure Sensors for Vertical Trajectory Determination

机译:集成MEMS惯性和压力传感器,用于垂直轨迹确定

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Integration of a low-cost global positioning system (GPS) with a microelectromechanical system-based inertial measurement unit (MEMS-IMU) is a widely used method that takes advantage of the individual superiority of each system to get a more accurate and robust navigation performance. However, because of poor observations as well as multipath effects, the GPS has low accuracy in the vertical direction. As a result, the navigation accuracy even in an integrated GPS/MEMS-IMU system is more challenged in the vertical direction than the horizontal direction. To overcome this problem, this paper investigates the integration of a MEMS barometric pressure sensor with the MEMS-IMU for vertical position/velocity tracking without the GPS that has applications in sports. A cascaded two-step Kalman filter consisting of separate orientation and position/velocity subsystems is proposed for this integration. Slow human movements in addition to more rapid sport activities such as vertical and step-down jumps can be tracked using the proposed algorithm. The height-tracking performance is benchmarked against a reference camera-based motion-tracking system and an error analysis is performed. The experimental results show that the vertical trajectory tracking error is less than 28.1 cm. For the determination of jump vertical height/drop, the proposed algorithm has an error of less than 5.8 cm.
机译:低成本全球定位系统(GPS)与基于微机电系统的惯性测量单元(MEMS-IMU)的集成是一种广泛使用的方法,该方法利用每个系统的独特优势来获得更准确,更强大的导航性能。但是,由于观测不良以及多径效应,GPS在垂直方向上的精度较低。结果,即使在集成的GPS / MEMS-IMU系统中,垂直方向上的导航精度也比水平方向上的挑战更大。为了克服这个问题,本文研究了将MEMS气压传感器与MEMS-IMU集成在一起以进行垂直位置/速度跟踪,而没有将GPS应用于体育运动的情况。为此集成提出了一个由独立的方向和位置/速度子系统组成的级联两步卡尔曼滤波器。使用提议的算法,除了可以跟踪诸如垂直跳和跳下跳高之类的较快速的运动活动之外,还可以跟踪缓慢的人类运动。相对于基于参考相机的运动跟踪系统对高度跟踪性能进行了基准测试,并执行了误差分析。实验结果表明,垂直轨迹跟踪误差小于28.1 cm。为了确定跳跃垂直高度/下降,所提出的算法具有小于5.8cm的误差。

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