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Navigation of autonomous underwater vehicle using extended kalman filter

DRS at CSIR-National Institute of Oceanography

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Title Navigation of autonomous underwater vehicle using extended kalman filter
 
Creator Ranjan, T.N.
Nherakkol, A.
Navelkar, G.S.
 
Subject underwater vehicle
kalman filter
underwater missions
 
Description To navigate the Autonomous Underwater Vehicle (AUV) accurately is one of the most important aspects in its application. A truly autonomous vehicle must determine its position which requires the optimal integration of all available attitude and velocity signals. This paper investigates the extended Kalman Filtering (EKF) method to merge asynchronous heading, attitude, velocity and Global Positioning System (GPS) information to produce a single state vector. Dead reckoning determines the vehicle’s position by calculating the distance travelled using its measured speed and time interval. The vehicle takes GPS fixes whenever available to reduce the position error and fuses the measurements for position estimation. The implementation of this algorithm with EKF provides better tracking of the trajectory for underwater missions of longer durations
 
Date 2011-03-07T05:50:02Z
2011-03-07T05:50:02Z
2010
 
Type Book Chapter
 
Identifier In "Trends in intelligent robotics". 13th FIRA Robot World Congress, FIRA 2010, Bangalore, India, September 15-17, 2010. Proceedings. eds. by: Vadakkepat, P.; Kim, J.-H.; Jesse, N.; Al Mamun, A.; Kiong, T.K.; Baltes, J.; Anderson, J.; Verner, I.; Ahlgren, D., Springer; New York; USA; 2010; 1-9
http://drs.nio.org/drs/handle/2264/3796
 
Language en
 
Rights Copyright [2011] Springer.
 
Publisher Springer