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Simultaneous Localization and Mapping in Wireless Sensor Networks

机译:无线传感器网络中的同时定位和映射

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摘要

Wireless sensors became smaller and cheaper in the recent years. Applications with thousands of nodes for tracking and monitoring are now feasible. Many of them require the knowledge about the locations of the sensors. The process of localization depends on estimating the position of the features within the environment. This paper proposes a novel algorithm to localize the sensors in any environment. Unlike any other technique like conventional SLAM, this new method does not require any architecture involving non-active beacons or mobile agents, such as robot. The new algorithm is presented that uses the sensors which act as active beacons themselves. The localization uses a least squares estimation (LSE), which processes the measured distances between the sensors. The distance measured was calculated based on received signal strength indicators (RSSI). Experiments were carried out in Mica2 Motes sensor networks. The estimated locations in the experiments were less then one meter away from the true locations which is an error of less than 10% of the transmission range from the sensors.
机译:近年来,无线传感器变得更小,更便宜。现在,具有数千个用于跟踪和监视的节点的应用程序是可行的。他们中的许多人需要有关传感器位置的知识。本地化的过程取决于估计环境中要素的位置。本文提出了一种新颖的算法来定位任何环境中的传感器。与其他任何技术(如常规SLAM)不同,此新方法不需要涉及非活动信标或移动代理(例如机器人)的任何体系结构。提出了一种新算法,该算法使用了本身充当主动信标的传感器。定位使用最小二乘估计(LSE),该最小二乘估计处理传感器之间的测量距离。根据接收信号强度指示器(RSSI)计算测得的距离。实验是在Mica2 Motes传感器网络中进行的。实验中的估计位置距离真实位置不到一米,这是小于传感器传输范围的10%的误差。

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