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A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle
A. Annamalai,
A. Motwani,
S.K. Sharma,
R. Sutton,
P. Culverhouse,
C. Yang,
Chenguang Yang
Journal of Navigation, Volume: 68, Issue: 04, Pages: 750 - 768
Swansea University Author: Chenguang Yang
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DOI (Published version): 10.1017/S0373463315000065
Abstract
In this paper, we propose a novel robust navigational approach to be integrated with the guidance and control systems of an uninhabitedsurface vehicle Springer. A weighted Interval Kalman Filter (wIKF) in used for waypoint tracking, and has been compared with that of one that uses a conventional Kal...
Published in: | Journal of Navigation |
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2015
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URI: | https://cronfa.swan.ac.uk/Record/cronfa27027 |
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2018-02-09T05:09:40Z |
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2018-01-10T17:53:41.0696721 v2 27027 2016-04-01 A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle d2a5024448bfac00a9b3890a8404380b Chenguang Yang Chenguang Yang true false 2016-04-01 In this paper, we propose a novel robust navigational approach to be integrated with the guidance and control systems of an uninhabitedsurface vehicle Springer. A weighted Interval Kalman Filter (wIKF) in used for waypoint tracking, and has been compared with that of one that uses a conventional Kalman Filter (KF) navigational design. The conventional KF fails to predict correctly the vehicle’s heading when there is unmodelled uncertainty of the sensing equipment, and thus would negatively affect the performance of subsequent navigation, guidance and control (NGC). While the proposed method using a wIKF technique enhances robustness with respect to erroneous modelling, and thus secures better accuracy and efficiency in completing a mission. Journal Article Journal of Navigation 68 04 750 768 31 7 2015 2015-07-31 10.1017/S0373463315000065 COLLEGE NANME COLLEGE CODE Swansea University 2018-01-10T17:53:41.0696721 2016-04-01T18:32:32.5120470 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised A. Annamalai 1 A. Motwani 2 S.K. Sharma 3 R. Sutton 4 P. Culverhouse 5 C. Yang 6 Chenguang Yang 7 0027027-01042016185732.pdf Annamalai.pdf 2016-04-01T18:57:32.9370000 Output 1757178 application/pdf Accepted Manuscript true 2016-05-17T00:00:00.0000000 true |
title |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
spellingShingle |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle Chenguang Yang |
title_short |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
title_full |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
title_fullStr |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
title_full_unstemmed |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
title_sort |
A Robust Navigation Technique for Integration in the Guidance and Control of an Uninhabited Surface Vehicle |
author_id_str_mv |
d2a5024448bfac00a9b3890a8404380b |
author_id_fullname_str_mv |
d2a5024448bfac00a9b3890a8404380b_***_Chenguang Yang |
author |
Chenguang Yang |
author2 |
A. Annamalai A. Motwani S.K. Sharma R. Sutton P. Culverhouse C. Yang Chenguang Yang |
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Journal article |
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Journal of Navigation |
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68 |
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Swansea University |
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10.1017/S0373463315000065 |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised |
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description |
In this paper, we propose a novel robust navigational approach to be integrated with the guidance and control systems of an uninhabitedsurface vehicle Springer. A weighted Interval Kalman Filter (wIKF) in used for waypoint tracking, and has been compared with that of one that uses a conventional Kalman Filter (KF) navigational design. The conventional KF fails to predict correctly the vehicle’s heading when there is unmodelled uncertainty of the sensing equipment, and thus would negatively affect the performance of subsequent navigation, guidance and control (NGC). While the proposed method using a wIKF technique enhances robustness with respect to erroneous modelling, and thus secures better accuracy and efficiency in completing a mission. |
published_date |
2015-07-31T06:54:08Z |
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1821387468179505152 |
score |
11.04748 |