Next Article in Journal
Time Reversal Acoustic Communication Using Filtered Multitone Modulation
Next Article in Special Issue
Commercial Motion Sensor Based Low-Cost and Convenient Interactive Treadmill
Previous Article in Journal
Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica
Previous Article in Special Issue
A Framework to Automate Assessment of Upper-Limb Motor Function Impairment: A Feasibility Study
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(9), 23536-23553;

A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario

College of Information Science and Engineering, Northeastern University, 110819 Shenyang, China
Author to whom correspondence should be addressed.
Academic Editor: Andreas König
Received: 7 July 2015 / Revised: 9 September 2015 / Accepted: 10 September 2015 / Published: 16 September 2015
(This article belongs to the Special Issue Integrated Intelligent Sensory Systems with Self-x Capabilities)
Full-Text   |   PDF [516 KB, uploaded 16 September 2015]   |  


Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes’ actual coordinates and target’s relative coordinates, the target’s actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS. View Full-Text
Keywords: Gaussian mixed model; multidimensional scaling; wireless sensor network; RSSI Gaussian mixed model; multidimensional scaling; wireless sensor network; RSSI

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Li, B.; Cui, W.; Wang, B. A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario. Sensors 2015, 15, 23536-23553.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top