A Novel Weighted Localization Method in Wireless Sensor Networks Based on Hybrid RSS/AoA Measurements

被引：21

作者：

Ding, Weizhong ^{[1
]}

Chang, Shengming ^{[1
]}

Li, Jun ^{[1
]}

机构：

[1] Ningbo Univ Technol, Sch Elect & Informat Engn, Ningbo 315211, Peoples R China

来源：

IEEE ACCESS | 2021年 / 9卷

关键词：

Location awareness; Wireless sensor networks; Noise measurement; Weight measurement; Measurement uncertainty; Estimation; Complexity theory; Wireless sensor networks (WSNs); weighted least square (WLS); received signal strength (RSS); angle of arrival (AOA); localization; TARGET LOCALIZATION; CLOSED-FORM; RSS; ESTIMATOR;

D O I：

10.1109/ACCESS.2021.3126148

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A hybrid RSS/AOA indoor localization method based on error variance and measurement noise weighted least squares (ENWLS) is proposed. This method is based on three-dimensional wireless sensor networks, and achieves high-precision indoor positioning without increasing its complexity. We use the first-order Taylor approximation to approximate the linear weighted least square (WLS) error, and use the weighted least squares estimation to roughly estimate the location of the target, then determine the weight matrix by estimating the linear WLS error variance and the measured noise value on the sensor node. Simulation results show that our proposed method is better than other existing hybrid RSS/AOA localization methods.

引用

页码：150677 / 150685

页数：9

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