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Twist-n-Sync:使用MEMS陀螺仪实现微秒级精度的软件时钟同步

Twist-n-Sync: Software Clock Synchronization with Microseconds Accuracy Using MEMS-Gyroscopes.

作者信息

Faizullin Marsel, Kornilova Anastasiia, Akhmetyanov Azat, Ferrer Gonzalo

机构信息

Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.

Software Engineering Department, Saint Petersburg State University, 199034 St. Petersburg, Russia.

出版信息

Sensors (Basel). 2020 Dec 24;21(1):68. doi: 10.3390/s21010068.

Abstract

Sensor networks require a high degree of synchronization in order to produce a stream of data useful for further purposes. Examples of time misalignment manifest as undesired artifacts when doing multi-camera bundle-adjustment or global positioning system (GPS) geo-localization for mapping. Network Time Protocol (NTP) variants of clock synchronization can provide accurate results, though present high variance conditioned by the environment and the channel load. We propose a new precise technique for software clock synchronization over a network of rigidly attached devices using gyroscope data. Gyroscope sensors, or IMU, provide a high-rate measurements that can be processed efficiently. We use optimization tools over the correlation signal of IMU data from a network of gyroscope sensors. Our method provides stable microseconds accuracy, regardless of the number of sensors and the conditions of the network. In this paper, we show the performance of the gyroscope software synchronization in a controlled environment, and we evaluate the performance in a sensor network of smartphones by our open-source Android App, Twist-n-Sync, that is publicly available.

摘要

传感器网络需要高度同步,以便生成对进一步用途有用的数据流。时间未对准的示例在进行多相机光束平差或用于地图绘制的全球定位系统(GPS)地理定位时表现为不期望的伪影。时钟同步的网络时间协议(NTP)变体可以提供准确的结果,尽管受环境和信道负载的影响存在高方差。我们提出了一种新的精确技术,用于在使用陀螺仪数据的刚性连接设备网络上进行软件时钟同步。陀螺仪传感器或惯性测量单元(IMU)提供可以高效处理的高速率测量值。我们对来自陀螺仪传感器网络的IMU数据的相关信号使用优化工具。我们的方法提供稳定的微秒级精度,而与传感器数量和网络条件无关。在本文中,我们展示了在受控环境中陀螺仪软件同步的性能,并通过我们公开可用的开源安卓应用Twist-n-Sync在智能手机传感器网络中评估了性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc0/7795013/f9a8eb7c59e9/sensors-21-00068-g001.jpg

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