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Feasibility Study and Performance Analysis of a Gyroless Orientation Tracker

机译:无陀螺定向仪的可行性研究与性能分析

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Inertial orientation tracking systems commonly use three types of sensors: accelerometers, magnetometers, and gyroscopes. The angular rate signal is used to obtain a dead reckoning estimate, whereas the gravitational and local magnetic field measures allow us to apply a correction and to obtain a drift-free result. Considering the present market of inertial MEMS sensors, the current consumption of gyroscopes represents a major part of the power budget of wireless inertial sensor nodes, which should be minimized given the mobility of the application. This paper introduces an orientation tracking algorithm, based on an unscented Kalman filter, that does not require angular rate data for tracking human movements up to 450 $^{circ}/hbox{s}$ , which is a reasonable value for many applications. Since accelerometers measure other accelerations beside gravity and magnetometers are prone to magnetic disturbances, adaptive techniques are applied in order to reduce the influence on the estimations. The performance of the system is quantitatively analyzed and compared to an estimator that includes angular rate information.
机译:惯性方向跟踪系统通常使用三种类型的传感器:加速度计,磁力计和陀螺仪。角速率信号用于获得航位推算估计,而重力和局部磁场测量则允许我们进行校正并获得无漂移的结果。考虑到惯性MEMS传感器的当前市场,陀螺仪的电流消耗是无线惯性传感器节点功率预算的主要部分,鉴于应用的灵活性,应将其最小化。本文介绍了一种基于无味卡尔曼滤波器的方向跟踪算法,该算法不需要角速率数据即可跟踪高达450 $ ^ circ / hbox {s} $的人体运动,这对于许多应用而言都是合理的值。由于加速度计会测量重力以外的其他加速度,而磁力计则容易产生磁干扰,因此应用了自适应技术以减少对估计的影响。对系统的性能进行定量分析,并将其与包含角速率信息的估计器进行比较。

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