|Table of Contents|

Citation:
　Pengyun Chen,Pengfei Zhang,Jianlong Chang,et al.Fast Extraction of Local Underwater Terrain Features for Underwater Terrain-Aided Navigation[J].Journal of Marine Science and Application,2019,(3):334-342.[doi:10.1007/s11804-019-00086-6]
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Fast Extraction of Local Underwater Terrain Features for Underwater Terrain-Aided Navigation

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Title:
Fast Extraction of Local Underwater Terrain Features for Underwater Terrain-Aided Navigation
Author(s):
Pengyun Chen1;  Pengfei Zhang1;  Jianlong Chang1;  Peng Shen2
Affilations:
Author(s):
Pengyun Chen1;  Pengfei Zhang1;  Jianlong Chang1;  Peng Shen2
1 College of Mechatronic Engineering, North University of China, Taiyuan 030051, China;
2 National Deep Sea Center, Qingdao 266237, China
Keywords:
Underwater terrain modeling; Beam selection; Mixing resolution; Terrain storage model; Index extraction
分类号:
-
DOI:
10.1007/s11804-019-00086-6
Abstract:
Terrain matching accuracy and real-time performance are affected by local underwater terrain features and structure of matching surface. To solve the extraction problem of local terrain features for underwater terrain-aided navigation (UTAN), real-time data model and selection method of beams are proposed. Then, an improved structure of terrain storage is constructed, and a fast interpolation strategy based on index is proposed, which can greatly improve the terrain interpolation-reconstruction speed. Finally, for the influences of tide, an elimination method of reference depth deviation is proposed, which can reduce the reference depth errors caused by tidal changes. As the simulation test shows, the proposed method can meet the requirements of real-time performance and effectiveness. Furthermore, the extraction time is considerably reduced, which makes the method suitable for the extraction of local terrain features for UTAN.

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Memo

Memo:
Received date:2017-11-24;Accepted date:2018-04-13。
Foundation item:This study is supported by the National Natural Science Foundation of China (Grant No. 51775518), Natural Science Foundation of North University of China (Grant No. 2017001), and the 333 Academic Start Funding for Talents of North University of China (Grant No. 13011915).
Corresponding author:Pengyun Chen,chenpengyun@nuc.edu.cn
Last Update: 2019-09-18