Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

An ADS-B Trajectory Segmentation Correction Algorithm Based on Improved Kalman Filtering

Authors
Boyuan Gong, Wenbo Li, Zhiyuan Shen
Corresponding Author
Boyuan Gong
Available Online November 2017.
DOI
10.2991/amms-17.2017.12How to use a DOI?
Keywords
component; ADS-B; surveillance systems; trajectory correction; segmentation; CA/CV model
Abstract

The Automatic Dependent Surveillance-Broadcast (ADS-B) with the advantage of faster update speed of the data, wider range of detection and sharing of traffic information. It has been regarded as one of the future mainstream surveillance systems by the International Civil Aviation Organization. This paper presents the conception, development and application of ADS-B. It also analyses the feature of the radar trajectory and ADS-B trajectory. Using CA/CV model, a new method based on improved Kalman filter to correct ADS-B trajectory is proposed to evaluate the surveillance performance based on trajectory segmentation, which is able to assess the integrity and accuracy of ADS-B data. The simulation results demonstrate the effectiveness of the proposed method.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
10.2991/amms-17.2017.12
ISSN
1951-6851
DOI
10.2991/amms-17.2017.12How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Boyuan Gong
AU  - Wenbo Li
AU  - Zhiyuan Shen
PY  - 2017/11
DA  - 2017/11
TI  - An ADS-B Trajectory Segmentation Correction Algorithm Based on Improved Kalman Filtering
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 54
EP  - 57
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.12
DO  - 10.2991/amms-17.2017.12
ID  - Gong2017/11
ER  -