Abstract
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.
Highlights
I N recent years, localization method plays an increasingly important role in wireless sensor networks (WSNs) [1]– [12]
The PLE changes according to the environmental conditions, so perfect knowledge of the PLE is virtually impossible to obtain in practice
This paper proposes an indoor target localization method, ENWLS, based on hybrid received signal strength (RSS)/angle of arrival (AOA) measurement in 3D wireless sensor networks
Summary
I N recent years, localization method plays an increasingly important role in wireless sensor networks (WSNs) [1]– [12]. WSNs are wireless networks composed of sensors. Thanks to GPS and cellular network, mobile terminal localization can achieve high accuracy. In indoor environment or with serious shadowing effect, satellite and cellular signals are often interrupted, and localization becomes a problem. This paper introduces an indoor location method based on WSNs. WSNs are composed of anchors which locations are known and targets which locations are unknown. The location of the targets are determined by the location of the anchors and the measurements of radio signals
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
