A Survey of Indoor Location Algorithms Based on AOA

A Survey of Indoor Location Algorithms Based on AOA
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基于AOA的室内定位算法综述

DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Ying He
Ying He
中科院分区：
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文献类型：
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作者：
Xue;Benshen Ji;Jian Wang;Lin Mei;Ying He

文献摘要

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室内定位算法因其在目标跟踪、人员定位等诸多新兴应用领域的广泛应用而成为近几十年来的研究热点。然而，成熟的商业产品仍然很受欢迎。本文提出并分析了三种具有代表性的、有效的室内定位算法--基于到达角的室内定位算法。这三种方法是平均法、加权最小二乘法(WLS)和基于聚类的方法。此外，还进行了大量的仿真实验，分析了它们的特点和性能。
Indoor location algorithm has become a research hotspot in the past decades for its wide applications, such as object tracking, personnel localization, and many other rising applications. Yet the mature commercial products are still in demand. In this paper, we present and analyze three representative and effective indoor location algorithms which are only based on angle of arrival (AOA). The three methods are the Averaging method, the Weighted Least Squares (WLS) method and the Clustering-based method. Moreover, a large number of simulation experiments are conducted to analyze their characteristics and performance.