Mobile Localization And Tracking With Los And Nlos Identification In Wireless Sensor Networks

Y. K. Benkouider; M. Keche

doi:10.21307/ijssis-2017-907

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Mobile Localization And Tracking With Los And Nlos Identification In Wireless Sensor Networks

International Journal on Smart Sensing and Intelligent Systems

Volume 9 (2016): Issue 2 (January 2016)

By: Y. K. Benkouider and M. Keche

Open Access

|Jun 2016

Abstract

This paper addresses the problem of mobile sensor localization and tracking in an obstructed environment. To solve this problem, a combination of three approaches is proposed: a nonlinear Kalman Filter to estimate the mobile position, a sub filter used jointly with the nonlinear filter to estimate the bias due to the Non-Line Of Sight (NLOS) effect and a low complexity method for Line Of Sight (LOS) and NLOS identification. Based on hypothesis testing, this method discriminates between the LOS and NLOS situations using a sequence of estimated biases. Simulation results show that the proposed method provides good positioning accuracy

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Articles in this issue

DOI: https://doi.org/10.21307/ijssis-2017-907 | Journal eISSN: 1178-5608

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Language: English

Page range: 1054 - 1072

Submitted on: Feb 22, 2016

Accepted on: Apr 11, 2016

Published on: Jun 1, 2016

Published by: Macquarie University, Australia

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Localization,

Tracking,

Wireless Sensor Network,

Non Line of Sight,

Divided Difference Kalman Filter,

Unscented Kalman Filter,

Bias estimation,

Hypothesis testing

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2016 Y. K. Benkouider, M. Keche, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 9 (2016): Issue 2 (January 2016)