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GPS/MEMS INS Data Fusion and Map Matching in Urban Areas
This paper presents an evaluation of the map-matching scheme of an integrated GPS/INS system in urban areas. Data fusion using a Kalman filter and map matching are effective approaches to improve the performance of navigation system applications based on GPS/MEMS IMUs. The study considers the curve-...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821347/ https://www.ncbi.nlm.nih.gov/pubmed/23979480 http://dx.doi.org/10.3390/s130911280 |
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author | Chu, Hone-Jay Tsai, Guang-Je Chiang, Kai-Wei Duong, Thanh-Trung |
author_facet | Chu, Hone-Jay Tsai, Guang-Je Chiang, Kai-Wei Duong, Thanh-Trung |
author_sort | Chu, Hone-Jay |
collection | PubMed |
description | This paper presents an evaluation of the map-matching scheme of an integrated GPS/INS system in urban areas. Data fusion using a Kalman filter and map matching are effective approaches to improve the performance of navigation system applications based on GPS/MEMS IMUs. The study considers the curve-to-curve matching algorithm after Kalman filtering to correct mismatch and eliminate redundancy. By applying data fusion and map matching, the study easily accomplished mapping of a GPS/INS trajectory onto the road network. The results demonstrate the effectiveness of the algorithms in controlling the INS drift error and indicate the potential of low-cost MEMS IMUs in navigation applications. |
format | Online Article Text |
id | pubmed-3821347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-38213472013-11-09 GPS/MEMS INS Data Fusion and Map Matching in Urban Areas Chu, Hone-Jay Tsai, Guang-Je Chiang, Kai-Wei Duong, Thanh-Trung Sensors (Basel) Article This paper presents an evaluation of the map-matching scheme of an integrated GPS/INS system in urban areas. Data fusion using a Kalman filter and map matching are effective approaches to improve the performance of navigation system applications based on GPS/MEMS IMUs. The study considers the curve-to-curve matching algorithm after Kalman filtering to correct mismatch and eliminate redundancy. By applying data fusion and map matching, the study easily accomplished mapping of a GPS/INS trajectory onto the road network. The results demonstrate the effectiveness of the algorithms in controlling the INS drift error and indicate the potential of low-cost MEMS IMUs in navigation applications. MDPI 2013-08-23 /pmc/articles/PMC3821347/ /pubmed/23979480 http://dx.doi.org/10.3390/s130911280 Text en © 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Chu, Hone-Jay Tsai, Guang-Je Chiang, Kai-Wei Duong, Thanh-Trung GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title | GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title_full | GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title_fullStr | GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title_full_unstemmed | GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title_short | GPS/MEMS INS Data Fusion and Map Matching in Urban Areas |
title_sort | gps/mems ins data fusion and map matching in urban areas |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821347/ https://www.ncbi.nlm.nih.gov/pubmed/23979480 http://dx.doi.org/10.3390/s130911280 |
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