Distributed linear combination estimators for localization based on received signal strength in wireless networks

Wei-Yu Chen, Scott L. Miller
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引用次数: 4

Abstract

Wireless geolocation problems based on received signal strength (RSS) are discussed in this paper. Using the maximum likelihood based range estimates, a new distributed and iterative linear combination location estimator is proposed. In a non-cooperative case where unknown-location (blindfolded) devices only utilize the power measurements from known-location devices (anchors), the proposed algorithm has a similar error performance to the maximum likelihood estimator but the computation time is much less. In cooperative localization, a blindfolded node uses information from not only anchors but also other blindfolded nodes. After being compared with the distributed maximum likelihood estimator and the distributed weighted-multidimensional scaling (dwMDS) method, it is recognized that the estimator performs well in accuracy, computation time, and the use of wireless transmissions under various wireless environments.
无线网络中基于接收信号强度定位的分布式线性组合估计
讨论了基于接收信号强度(RSS)的无线定位问题。利用基于最大似然的距离估计,提出了一种新的分布式迭代线性组合位置估计方法。在未知位置(蒙眼)设备仅利用已知位置设备(锚点)的功率测量的非合作情况下,该算法具有与最大似然估计器相似的误差性能,但计算时间要少得多。在协同定位中,一个被蒙住眼睛的节点不仅使用锚点的信息,还使用其他被蒙住眼睛的节点的信息。通过与分布式极大似然估计方法和分布式加权多维尺度(dwMDS)方法的比较,认为该估计方法在精度、计算时间和各种无线环境下的无线传输使用方面都有良好的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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