eprintid: 1421172
rev_number: 63
eprint_status: archive
userid: 608
dir: disk0/01/42/11/72
datestamp: 2014-03-18 09:28:38
lastmod: 2021-12-20 00:45:55
status_changed: 2015-03-17 16:34:32
type: proceedings_section
metadata_visibility: show
item_issues_count: 0
creators_name: Wang, L
title: Kinematic GNSS Shadow Matching Using Particle Filters
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
abstract: Student Paper Award Winner. The poor performance of GNSS user equipment in urban canyons is a well-known problem and is particularly inaccurate in the cross-street direction. However, the accuracy in this direction greatly affects many applications, including vehicle lane identification and high-accuracy pedestrian navigation. Shadow matching was proposed to help solve this problem by using information derived from 3D models of buildings. Though users of GNSS positioning typically move, previous research has focused on static shadow-matching positioning. In this paper, for the first time, kinematic shadow-matching positioning is tackled. Kalman filter based shadow matching is proposed and also, in order to overcome some of its predicted limitations, a particle filter is proposed to better solve the problem.
date: 2014-09-12
publisher: The Institute of Navigation
official_url: http://www.ion.org/publications/browse.cfm?proceedingsID=85
vfaculties: VENG
oa_status: green
full_text_type: other
primo: open
primo_central: open_green
verified: verified_manual
elements_source: Manually entered
elements_id: 935421
lyricists_name: Wang, Lei
lyricists_id: LWANG11
full_text_status: public
place_of_pub: Manassas, US
pagerange: 1907 - 1919
event_title: ION GNSS+ 2014
event_location: Tampa, Florida
event_dates: 2014-09-08 - 2014-09-12
book_title: Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2014)
citation:        Wang, L;      (2014)    Kinematic GNSS Shadow Matching Using Particle Filters.                     In:  Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2014).  (pp. 1907 - 1919).  The Institute of Navigation: Manassas, US.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1421172/1/GNSS14-0181.pdf