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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Fine-Grained Localization for Multiple Transceiver-Free Objects by using RF-Based Technologies
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Fine-Grained Localization for Multiple Transceiver-Free Objects by using RF-Based Technologies

机译:使用基于RF的技术对多个无收发器的对象进行精细定位

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摘要

In traditional radio-based localization methods, the target object has to carry a transmitter (e.g., active RFID), a receiver (e.g., 802.11$times$ detector), or a transceiver (e.g., sensor node). However, in some applications, such as safe guard systems, it is not possible to meet this precondition. In this paper, we propose a model of signal dynamics to allow the tracking of a transceiver-free object. Based on radio signal strength indicator (RSSI), which is readily available in wireless communication, three centralized tracking algorithms, and one distributed tracking algorithm are proposed to eliminate noise behaviors and improve accuracy. The midpoint and intersection algorithms can be applied to track a single object without calibration, while the best-cover algorithm has higher tracking accuracy but requires calibration. The probabilistic cover algorithm is based on distributed dynamic clustering. It can dramatically improve the localization accuracy when multiple objects are present. Our experimental test-bed is a grid sensor array based on MICA2 sensor nodes. The experimental results show that the localization accuracy for single object can reach about 0.8 m and for multiple objects is about 1 m.
机译:在传统的基于无线电的定位方法中,目标对象必须携带发送器(例如,有源RFID),接收器(例如,802.11×检测器)或收发器(例如,传感器节点)。但是,在某些应用中,例如安全防护系统,不可能满足此先决条件。在本文中,我们提出了一种信号动力学模型,可以跟踪无收发器的物体。基于无线通信中易于使用的无线电信号强度指示器(RSSI),提出了三种集中式跟踪算法和一种分布式跟踪算法,以消除噪声行为并提高准确性。中点和相交算法可用于跟踪单个对象而无需校准,而最佳覆盖算法具有更高的跟踪精度,但需要校准。概率覆盖算法基于分布式动态聚类。当存在多个物体时,它可以极大地提高定位精度。我们的实验台是基于MICA2传感器节点的网格传感器阵列。实验结果表明,单个物体的定位精度约为0.8 m,而多个物体的定位精度约为1 m。

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