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Bayesian Time Delay Estimation of GNSS Signals in Dynamic Multipath Environments

Lentmaier, Michael and Krach, Bernhard and Robertson, Patrick (2007) Bayesian Time Delay Estimation of GNSS Signals in Dynamic Multipath Environments. International Journal of Navigation and Observation. Hindawi Publishing Corporation. DOI: 10.1155/IJNO.

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Official URL: http://www.hindawi.com/journals/ijno/

Abstract

A sequential Bayesian estimation algorithm for multipath mitigation is presented, with an underlying movement model that is especially designed for dynamic channel scenarios. In order to facilitate efficient integration into receiver tracking loops, it builds upon complexity reduction concepts that previously have been applied within maximum likelihood (ML) estimators. To demonstrate its capabilities under different GNSS signal conditions, simulation results are presented for both BPSK modulated and BOC(1,1) modulated navigation signals.

Document Type:Article
Title:Bayesian Time Delay Estimation of GNSS Signals in Dynamic Multipath Environments
Authors:
AuthorsInstitution or Email of Authors
Lentmaier, MichaelTU Dresden
Krach, BernhardUNSPECIFIED
Robertson, PatrickUNSPECIFIED
Date:1 August 2007
Journal or Publication Title:International Journal of Navigation and Observation
DOI:10.1155/IJNO
Publisher:Hindawi Publishing Corporation
Series Name:Special Issue on Future GNSS Signals
Status:Published
Keywords:Global Navigation Satellite Systems, Signal Parameter Estimation, Bayesian Estimation, Maximum Likelihood Estimation, Multipath Mitigation, Synchronization.
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W KN - Kommunikation/Navigation
DLR - Research area:Space
DLR - Program:W KN - Kommunikation/Navigation
DLR - Research theme (Project):W - Vorhaben GNSS2/Neue Dienste und Produkte (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation
Deposited By: Bernhard Krach
Deposited On:13 Jun 2008
Last Modified:12 Dec 2013 20:30

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