Title
Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays.
Abstract
To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region.
Year
DOI
Venue
2018
10.3390/s18041044
SENSORS
Keywords
Field
DocType
underwater technology,marine navigation,adaptive filters,cooperative systems,polar region,Unmanned Underwater Vehicles (UUV)
Inertial navigation system,Underwater acoustic communication,Algorithm,Kalman filter,Rapid convergence,Adaptive filter,Polar,Engineering,Grid,Underwater
Journal
Volume
Issue
ISSN
18
4.0
1424-8220
Citations 
PageRank 
References 
1
0.36
8
Authors
6
Name
Order
Citations
PageRank
Zheping Yan1108.07
Lu Wang2132.60
Tongda Wang361.24
Zewen Yang423.45
Tao Chen54921.43
Jian Xu622455.55