Indoor positioning based on statistical multipath channel modeling

Chia Pang Yen; Peter J. Voltz

doi:10.1186/1687-1499-2011-189

Indoor positioning based on statistical multipath channel modeling

Chia Pang Yen, Peter J. Voltz

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In order to estimate the location of an indoor mobile station (MS), estimated time-of-arrival (TOA) can be obtained at each of several access points (APs). These TOA estimates can then be used to solve for the location of the MS. Alternatively, it is possible to estimate the location of the MS directly by incorporating the received signals at all APs in a direct estimator of position. This article presents a deeper analysis of a previously proposed maximum likelihood (ML)-TOA estimator, including a uniqueness property and the behavior in nonline-of-sight (NLOS) situations. Then, a ML direct location estimation technique utilizing all received signals at the various APs is proposed based on the ML-TOA estimator. The Cramer-Rao lower bound (CRLB) is used as a performance reference for the ML direct location estimator.

Original language	English (US)
Article number	189
Journal	Eurasip Journal on Wireless Communications and Networking
Volume	2011
Issue number	1
DOIs	https://doi.org/10.1186/1687-1499-2011-189
State	Published - Dec 1 2011

Keywords

direct location estimation
indoor positioning
maximum likelihood (ML)
time-of-arrival (TOA)

ASJC Scopus subject areas

Signal Processing
Computer Science Applications
Computer Networks and Communications

Access to Document

10.1186/1687-1499-2011-189

Cite this

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title = "Indoor positioning based on statistical multipath channel modeling",

abstract = "In order to estimate the location of an indoor mobile station (MS), estimated time-of-arrival (TOA) can be obtained at each of several access points (APs). These TOA estimates can then be used to solve for the location of the MS. Alternatively, it is possible to estimate the location of the MS directly by incorporating the received signals at all APs in a direct estimator of position. This article presents a deeper analysis of a previously proposed maximum likelihood (ML)-TOA estimator, including a uniqueness property and the behavior in nonline-of-sight (NLOS) situations. Then, a ML direct location estimation technique utilizing all received signals at the various APs is proposed based on the ML-TOA estimator. The Cramer-Rao lower bound (CRLB) is used as a performance reference for the ML direct location estimator.",

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Indoor positioning based on statistical multipath channel modeling

Abstract

Keywords

ASJC Scopus subject areas

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