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Low-Cost MEMS-Based Pedestrian Navigation Technique for GPS-Denied Areas

机译:基于GPS的低成本MEMS行人导航技术

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摘要

The progress in the micro electro mechanical system (MEMS) sensors technology in size, cost, weight, and power consumption allows for new research opportunities in the navigation field. Today, most of smartphones, tablets, and other handheld devices are fully packed with the required sensors for any navigation system such as GPS, gyroscope, accelerometer, magnetometer, and pressure sensors. For seamless navigation, the sensors' signal quality and the sensors availability are major challenges. Heading estimation is a fundamental challenge in the GPS-denied environments; therefore, targeting accurate attitude estimation is considered significant contribution to the overall navigation error. For that end, this research targets an improved pedestrian navigation by developing sensors fusion technique to exploit the gyroscope, magnetometer, and accelerometer data for device attitude estimation in the different environments based on quaternion mechanization. Results indicate that the improvement in the traveled distance and the heading estimations is capable of reducing the overall position error to be less than 15 m in the harsh environments.
机译:微机电系统(MEMS)传感器技术在尺寸,成本,重量和功耗方面的进步为导航领域提供了新的研究机会。如今,大多数智能手机,平板电脑和其他手持设备已完全装有任何导航系统所需的传感器,例如GPS,陀螺仪,加速度计,磁力计和压力传感器。对于无缝导航,传感器的信号质量和传感器可用性是主要挑战。在GPS受限的环境中,航向估计是一项基本挑战。因此,以精确的姿态估计为目标被认为是对整个导航误差的重要贡献。为此,本研究旨在通过开发传感器融合技术来改进行人导航,以利用陀螺仪,磁力计和加速度计数据在基于四元数机械化的不同环境中估计设备的姿态。结果表明,在恶劣环境下,行进距离和航向估计值的改善能够将整体位置误差减小到小于15 m。

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