TY - GEN
T1 - Robust 2d Indoor Positioning Algorithm in the Presence of Non-Line-of-Sight Signals
AU - AlSharif, Mohammed H.
AU - Ahmed, Mohanad
AU - Felemban, Abdulwahab
AU - Zayat, Abdullah
AU - Muqaibel, Ali
AU - Masood, Mudassir
AU - Al-Naffouri, Tareq Y.
N1 - KAUST Repository Item: Exported on 2020-12-22
PY - 2020/12/18
Y1 - 2020/12/18
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/666538
UR - https://ieeexplore.ieee.org/document/9287812/
U2 - 10.23919/Eusipco47968.2020.9287812
DO - 10.23919/Eusipco47968.2020.9287812
M3 - Conference contribution
SN - 978-1-7281-5001-7
BT - 2020 28th European Signal Processing Conference (EUSIPCO)
PB - IEEE
ER -