Dynamic Multipath Estimation by Sequential Monte Carlo Methods
(2007) International Technical Meeting of the Institute of Navigation Satellite Division, (ION GNSS), 2007 p.1712-1721- 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 artificially generated random channels and high resolution channel impulse responses recorded during a measurement campaign.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3731411
- author
- Lentmaier, Michael LU ; Krach, Bernhard and Thiasiriphet, Thanawat
- organization
- publishing date
- 2007
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- GNSS, positioning, multipath mitigation
- pages
- 1712 - 1721
- conference name
- International Technical Meeting of the Institute of Navigation Satellite Division, (ION GNSS), 2007
- conference location
- Forth Worth, TX, United States
- conference dates
- 2007-09-25 - 2007-09-28
- external identifiers
-
- scopus:58449134194
- language
- English
- LU publication?
- no
- id
- 06064b18-b8da-4d35-8692-ce7bcd58cc3d (old id 3731411)
- date added to LUP
- 2016-04-04 14:07:49
- date last changed
- 2022-02-06 18:52:13
@misc{06064b18-b8da-4d35-8692-ce7bcd58cc3d,
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 artificially generated random channels and high resolution channel impulse responses recorded during a measurement campaign.}},
author = {{Lentmaier, Michael and Krach, Bernhard and Thiasiriphet, Thanawat}},
keywords = {{GNSS; positioning; multipath mitigation}},
language = {{eng}},
pages = {{1712--1721}},
title = {{Dynamic Multipath Estimation by Sequential Monte Carlo Methods}},
year = {{2007}},
}