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

Weizhong Ding; Shengming Chang; Jun Li

doi:10.1109/ACCESS.2021.3126148

IEEE Access (Jan 2021)

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

Weizhong Ding,
Shengming Chang,
Jun Li

Affiliations

Weizhong Ding: ORCiD; School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China
Shengming Chang: ORCiD; School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China
Jun Li: ORCiD; School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, China

DOI: https://doi.org/10.1109/ACCESS.2021.3126148
Journal volume & issue: Vol. 9
pp. 150677 – 150685

Abstract

Read online

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.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

About the journal

Abstract

Keywords