2002Unpublished venueRequires access

Non-line-of-sight error mitigation in TDOA mobile location

Cong Li, Weihua Zhuang

Open publisher page 194 citations

Abstract

We investigate the non-line-of-sight (NLOS) propagation identification and correction for time difference of arrival (TDOA) based mobile user location in wireless communication systems. Based on the defined TDOA residual, an NLOS base station identification algorithm is proposed. Different choices of the reference location for the residual calculation are compared via simulation. To correct the NLOS error with a certain distribution, we propose a maximum likelihood (ML) estimator for TDOA location systems. Simulation results demonstrate that the proposed NLOS recovering algorithm performs better than that using only LOS measurements, especially when the number of available base stations is small and/or the LOS base stations have an undesirable geometric layout.

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What this paper is about

We investigate the non-line-of-sight (NLOS) propagation identification and correction for time difference of arrival (TDOA) based mobile user location in wireless communication systems. Based on the defined TDOA residual, an NLOS base station identification algorithm is proposed. Different choices of the reference location for the residual calculation are compared via simulation. To correct the NLOS error with a certain distribution, we propose a maximum likelihood (ML) estimator for TDOA location systems. Simulation results demonstrate that the proposed NLOS recovering algorithm performs better than that using only LOS measurements, especially when the number of available base stations is small and/or the LOS base stations have an undesirable geometric layout.

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Available abstract

We investigate the non-line-of-sight (NLOS) propagation identification and correction for time difference of arrival (TDOA) based mobile user location in wireless communication systems. Based on the defined TDOA residual, an NLOS base station identification algorithm is proposed. Different choices of the reference location for the residual calculation are compared via simulation. To correct the NLOS error with a certain distribution, we propose a maximum likelihood (ML) estimator for TDOA location systems. Simulation results demonstrate that the proposed NLOS recovering algorithm performs better than that using only LOS measurements, especially when the number of available base stations is small and/or the LOS base stations have an undesirable geometric layout.

Key concepts: Non-line-of-sight propagation, Multilateration, Computer science, Base station, FDOA, Estimator, Residual, Identification (biology)

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