Robust 2d Indoor Positioning Algorithm in the Presence of Non-Line-of-Sight Signals

Mohammed H. AlSharif, Mohanad Ahmed, Abdulwahab Felemban, Abdullah Zayat, Ali Muqaibel, Mudassir Masood, Tareq Y. Al-Naffouri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The presence of non-line-of-sight (NLOS) signals in indoor positioning systems can severely degrade the positioning accuracy. This paper proposes a novel and computationally efficient algorithm to determine the line-of-sight (LOS) signals and the 2D position of a target in an indoor positioning system. The proposed algorithm was evaluated by simulating an indoor positioning system in 8 m × 8 m room under the presence of NLOS signals. When benchmarked with COFFEE and Triangle-Inequality methods, the proposed method shows significant improvement in computational time (151ms to 768ms) and marginal improvements over COFFEE in terms of F1-Score (at least 5% gain in F1-Score). The 2D position estimates are in less than 4.1 cm mean squared error. Moreover, the proposed algorithm was evaluated experimentally using a low-cost ultrasonic hardware.
Original languageEnglish (US)
Title of host publication2020 28th European Signal Processing Conference (EUSIPCO)
PublisherIEEE
ISBN (Print)978-1-7281-5001-7
DOIs
StatePublished - Dec 18 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-12-22

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