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Consistency-Based On-line Localization in Sensor Networks

机译:传感器网络中基于一致性的在线本地化

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摘要

We have developed a new on-line error modeling and optimization-based localization approach for sensor networks in the presence of distance measurement noise. The approach is solely based on the concept of consistency, and is developed specifically for the case of on-line localization, which refers to the situation when references are not available a priori. The localization problem is formulated as the task of maximizing the consistency between measurements and calculated distances. In addition, we also present a localized localization algorithm where a specified communication cost or the location accuracy is guaranteed while optimizing the other. We evaluated the approach in (ⅰ) both GPS-based and GPS-less scenarios; (ⅱ) 1-D, 2-D and 3-D spaces, on sets of acoustic ranging-based distance measurements recorded by deployed sensor networks. The experimental evaluation indicates that localization of only a few centimeters is consistently achieved when the average and median distance measurement errors are more than a meter, even when the nodes have only a few distance measurements. The relative performance in terms of location accuracy compares favorably with respect to several state-of-the-art localization approaches. Finally, several insightful observations about the required conditions for accurate location discovery are deduced by analyzing the experimental results.
机译:在存在距离测量噪声的情况下,我们为传感器网络开发了一种新的基于在线错误建模和优化的定位方法。该方法仅基于一致性的概念,专门针对在线本地化的情况而开发,在线本地化是指先验无法获得参考文献的情况。定位问题被表述为最大化测量值与计算出的距离之间的一致性的任务。此外,我们还提出了一种本地化的定位算法,在保证指定的通信成本或位置准确性的同时优化其他算法。我们在(ⅰ)基于GPS和无GPS的情况下评估了该方法; (ⅱ)1-D,2-D和3-D空间,位于已部署的传感器网络记录的基于声音测距的距离测量集上。实验评估表明,当平均和中位距离测量误差大于一米时,即使节点只有很少的距离测量值,也只能一致地实现几厘米的定位。就位置精度而言,相对性能相对于几种最新的定位方法具有优势。最后,通过分析实验结果,得出了一些关于准确定位所需条件的有见地的观察。

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