基于均匀圆形阵列的复杂室内环境近场源定位

Xiansheng Guo, Baocang Li, L. Chu, Disong Wang
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引用次数: 3

摘要

本文提出了一种基于均匀圆形阵列(UCA)的协方差矩阵匹配技术,用于室内多径环境下近场源的定位。首先,我们利用离线测量的协方差矩阵来获取合适间隔的参考点,并将这些矩阵存储为指纹;其次,设计了一种矩阵匹配算法来获取源的位置;与接收信号强度(RSS)指纹相比,协方差矩阵能提供更多的室内环境信道信息,因此本文算法在定位精度上优于基于RSS的算法。仿真结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-field source localization in complex indoor environment using uniform circular array
In this paper, we propose a covariance matrix matching technique using a uniform circular array (UCA) to localize a near-field source in indoor multi-path environment. Firstly, we exploit off-line measured covariance matrices for suitable spaced reference points and storing these matrices as a fingerprint; Secondly, a matrix matching algorithm is designed to obtain the position of source. Compared with received signal strength (RSS) fingerprint, covariance matrix can offer more channel information of indoor environment, hence, our proposed algorithm outperforms RSS based algorithm in accuracy of localization. Finally, some simulation results show the efficacy of our proposed technique.
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