基于泰勒级数展开和极大似然估计的室内定位算法

Wei Ni, G. Shen, Xiaobing Leng, L. Gui
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引用次数: 11

摘要

通过泰勒级数展开,室内阴影衰落的影响近似于测量传播距离的附加高斯误差。此外,多次测量的平均值有望减小高斯误差的方差。通过这种方法,可以解决无线室内定位的关键问题,即大阴影衰落。仿真和实验结果表明,该算法是有效的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Indoor Location Algorithm Based on Taylor Series Expansion and Maximum Likelihood Estimation
With Taylor series expansion, the effect of indoor shadowing fading is approximate to additional Gaussian errors of measured propagation distances. Further the average of multiple measurements is expected to decrease the variance of the Gaussian errors. By this means, the key issue in wireless indoor location, large shadowing fading, can be handled. Both simulations and experimental results reveal that this algorithm is effective
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