A new multi-sensor hierarchical data fusion algorithm based on unscented Kalman filter for the attitude observation of the wave glider-Reference-Cited by-同舟云学术

A new multi-sensor hierarchical data fusion algorithm based on unscented Kalman filter for the attitude observation of the wave glider

Published:2021-04 Issue: Volume:109 Page:102562
ISSN:0141-1187
Container-title:Applied Ocean Research
language:en
Short-container-title:Applied Ocean Research

Author:

Liu Fen,Liu Yubing,Sun Xiujun,Sang Hongqiang

Funder

Tianjin Municipal Natural Science Foundation

Publisher

Elsevier BV

Subject

Ocean Engineering

Reference34 articles.

1. A state optimization model based on Kalman filtering and robust estimation theory for fusion of multi-source information in highly non-linear systems;Adeel. A;Sensors,2019

2. Novel adaptive fuzzy extended Kalman filter for attitude estimation in GPS-denied environment;Assad;Giroskopiya I Navigatsiya,2019

3. A dual adaptive filtering approach for nonlinear finite element model updating accounting for modeling uncertainty;Astroza;Mech. Syst. Signal Proc.,2019

4. A review of data fusion techniques;Castanedo;Sci. World J.,2013

5. Fish spawning aggregations dynamics as inferred from a novel, persistent presence robotic approach;Chérubin;Front Mar. Sci.,2020

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